| 1. |
- Altinay, Doreen, et al.
(author)
-
On the estimation of extrinsic and intrinsic parameters for optical microscope calibration
- 2010
-
In: Proc. 2010 International Conference on Digital Image Computing: Techniques and Applications (DICTA). - 9781424488162 ; , s. 190 - 195
-
Conference paper (peer-reviewed)abstract
- This paper compares several camera calibration methods on the estimation of specific extrinsic and intrinsic parameters. Good estimates of the chosen parameters, rotation and radial lens distortion are essential to increase the accuracy of quantitative measurements and to accurately stitch single field-of-view-based images together. The parameters are obtained using two selected methods on different objective magnifications on a microscope system using a fixed grid calibration pattern. We evaluate two methods and show that the rotation angles from one of the methods is consistent with a simple homography while the other estimates a consistently smaller angle. The radial distortion estimates are both very small and relate to a distortion of less than one pixel.
|
|
| 2. |
- Gal, Yaniv, et al.
(author)
-
A new denoising method for dynamic contrast-enhanced MRI
- 2008
-
In: Proc. 2008 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - 9781424418145 ; , s. 847 - 850
-
Conference paper (peer-reviewed)abstract
- This paper presents a new algorithm for denoising dynamic contrast-enhanced (DCE) MR images. The algorithm is called Dynamic Non-Local Means and is a novel variation on the Non-Local Means (NL-Means) algorithm. It exploits the redundancy of information in the DCE-MRI sequence of images. An evaluation of the performance of the algorithm relative to six other denoising algorithms—Gaussian filtering, the original NL-Means algorithm, bilateral filtering, anisotropic diffusion filtering, the wavelets adaptive multiscale products threshold method, and the traditional wavelet thresholding method—is also presented. The evaluation was performed by two groups of expert observers—18 signal/image processing experts, and 9 clinicians (8 radiographers and 1 radiologist)—using real DCE-MRI data. The results of the evaluation provide evidence, at the α=0.05 level of significance, that both groups of observers deem the DNLM algorithm to perform visually better than all of the other algorithms.
|
|
| 3. |
- Gal, Yaniv, et al.
(author)
-
An evaluation of four parametric models of contrast enhancement for dynamic magnetic resonance imaging of the breast
- 2007
-
In: Proc. 2007 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - 9781424407873 ; , s. 71 - 74
-
Conference paper (peer-reviewed)abstract
- This paper presents an empirical evaluation of the goodness-of-fit (GOF) of four parametric models of contrast enhancement for dynamic resonance imaging of the breast: the Tofts, Brix, and Hayton pharmacokinetic models, and a novel empiric model. The goodness-of-fit of each model was evaluated with respect to: (i) two model-fitting algorithms (Levenberg- Marquardt and Nelder-Mead) and two fitting tolerances; and (ii) temporal resolution. In the first case the GOF was measured using data from three dynamic contrast-enhanced (DCE) MRI data sets from routine clinical examinations: one case with benign enhancement, one with malignant enhancement, and one with normal findings. Results are presented for fits to both the whole breast volume and to a selected region of interest. In the second case the GOF was measured by first fitting the models to several temporally sub-sampled versions of a custom high temporal resolution data set (subset of the breast volume containing a malignant lesion), and then comparing the fitted results to the original full temporal resolution data. Our results demonstrate that under the various optimization conditions considered, in general, both the proposed empiric model and the Hayton model fit the data equally well and that both of these models fit the data better than the Tofts and Brix models.
|
|
| 4. |
- Gal, Yaniv, et al.
(author)
-
Automatic segmentation of enhancing breast tissue in dynamic contrast-enhanced MR images
- 2007
-
In: Proc. 2007 Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA). - 0769530672 ; , s. 124-129
-
Conference paper (peer-reviewed)abstract
- We present a novel method for the segmentation of enhancing breast tissue, suspicious of malignancy, in dynamic contrast-enhanced (DCE) MR images. The method is based on seeded region growing and merging using criteria based on both the original image intensity values and the fitted parameters of a novel empiric parametric model of contrast enhancement. We present the results of the application of the method to DCE-MRI data sets originating from breast MRI examinations of 24 subjects (10 cases of benign and 14 cases of malignant enhancement). The results show that the segmentation method has 100% sensitivity for the detection of suspicious regions independently identified by a radiologist. The results suggest that the method has potential both as a tool to assist the clinician with the task of locating suspicious tissue and as input to a computer assisted diagnostic system for generating quantitative features for automatic classification of suspicious tissue.
|
|
| 5. |
- Gal, Yaniv, et al.
(author)
-
Feature and classifier selection for automatic classification of lesions in dynamic contrast-enhanced MRI of the breast
- 2009
-
In: Proc. 2009 International Conference on Digital Image Computing: Techniques and Applications (DICTA). - 9781424452972 ; , s. 132 - 139
-
Conference paper (peer-reviewed)abstract
- The clinical interpretation of breast MRI remains largely subjective, and the reported findings qualitative. Although the sensitivity of the method for detecting breast cancer is high, its specificity is poor. Computerised interpretation offers the possibility of improving specificity through objective quantitative measurement. This paper reviews the plethora of such features that have been proposed and presents a preliminary study of the most discriminatory features for dynamic contrast-enhanced MRI of the breast. In particular the results of a feature/classifier selection experiment are presented based on 20 lesions (10 malignant and 10 benign) from 20 routine clinical breast MRI examinations. Each lesion was segmented manually by a clinical radiographer and its diagnostic status confirmed by cytopathology or histopathology. The results show that textural and kinetic, rather than morphometric, features are the most important for lesion classification. They also show that the SVM classifier with sigmoid kernel performs better than other well-known classifiers: Fisher's linear discriminant function, Bayes linear classifier, logistic regression, and SVM with other kernels (distance, exponential, and radial).
|
|
| 6. |
- Gal, Yaniv, et al.
(author)
-
New Spatiotemporal Features for Improved Discrimination of Benign and Malignant Lesions in Dynamic Contrast-Enhanced-Magnetic Resonance Imaging of the Breast
- 2011
-
In: Journal of Computer Assisted Tomography. - 1532-3145 .- 0363-8715. ; 35:5, s. 645-652
-
Journal article (peer-reviewed)abstract
- Objectives: The objective of this study was to measure the efficacy of 7 new spatiotemporal features for discriminating between benign and malignant lesions in dynamic contrast-enhanced-magnetic resonance imaging (MRI) of the breast.Methods: A total of 48 breast lesions from 39 patients were used: 25 malignant and 23 benign. Lesions were acquired using 1.5-T MRI machines in 3 different protocols. Two experiments were performed: (i) selection of the most discriminatory subset of features drawn from the new features and features from the literature and (ii) validation of classification performance of the selected subset of features.Results: Results of the feature selection experiment show that the subset comprising 2 of the new features is the most useful for automatic classification of suspicious lesions in the breast: (i) gradient correlation of maximum intensity and (ii) mean wash-in rate. Results of the validation experiment show that using these 2 features, unseen data can be classified with an area under the receiver operating characteristic curve of 0.91 ± 0.06.Conclusions: Results of the experiments suggest that suspicious lesions in dynamic contrast-enhanced-MRI of the breast can be classified, with high accuracy, using only 2 of the proposed spatiotemporal features. The selected features indicate heterogeneity of enhancement and speed of enhancement in a tissue. High values of these indicators are likely to be correlated with malignancy.
|
|
| 7. |
- Hill, Andrew, et al.
(author)
-
A fast, segmentation-free, method for constructing a biomechanical model of the breast from DCE-MRI data
- 2008
-
In: Proc. 2008 International Conference on Digital Image Computing: Techniques and Applications (DICTA). - 9780769534565 ; , s. 386 - 391
-
Conference paper (peer-reviewed)abstract
- This paper presents a method for constructing a biomechanical breast model which does not require an initial time- and labour-intensive segmentation of the breast tissue. This is achieved by mapping voxel intensity and enhancement levels directly to Youngpsilas modulus values characteristic of the respective tissues. We demonstrate this new method by incorporating it into a biomechanically based registration evaluation framework, which produces qualitatively the same results as a segmentation based model.
|
|
| 8. |
- Hill, Andrew, et al.
(author)
-
Dynamic breast MRI: Image registration and its impact on enhancement curve estimation
- 2006
-
In: Proc. 2006 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - 1424400325 ; , s. 3049 - 3052
-
Conference paper (peer-reviewed)abstract
- A novel algorithm for performing registration of dynamic contrast-enhanced (DCE) MRI data of the breast is presented. It is based on an algorithm known as iterated dynamic programming originally devised to solve the stereo matching problem. Using artificially distorted DCE-MRI breast images it is shown that the proposed algorithm is able to correct for movement and distortions over a larger range than is likely to occur during routine clinical examination. In addition, using a clinical DCE-MRI data set with an expertly labeled suspicious region, it is shown that the proposed algorithm significantly reduces the variability of the enhancement curves at the pixel level yielding more pronounced uptake and washout phases
|
|
| 9. |
- Hill, Andrew, et al.
(author)
-
Edge intensity normalization as a bias field correction during balloon snake segmentation of breast MRI
- 2008
-
In: Proc. 2008 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - 1557-170X. ; , s. 3040 - 3043
-
Conference paper (peer-reviewed)abstract
- Segmentation of fat suppressed dynamic contrast enhanced MRI (DCE-MRI) image data can pose significant problems because of the inherently poor signal-to-noise ratio (SNR) and intensity variations due to the bias field. Segmentation methods such as balloon snakes, while able to operate in a poor SNR environment, are sensitive to variations in edge intensity, which are regularly encountered within DCE-MRI due to the bias field. In order to overcome the effects of the bias field, an intensity normalization based on the strength of the strongest edge, i.e. the skin-air-boundary, is proposed and evaluated. This normalization allows balloon segmentations to be run three times faster while maintaining, or even improving accuracy.
|
|
| 10. |
- Mehnert, Andrew, 1967, et al.
(author)
-
Registration evaluation of dynamic breast MR images
- 2005
-
In: Proceedings of the APRS Workshop on Digital Image Computing (WDIC2005). ; , s. 21-26
-
Conference paper (peer-reviewed)abstract
- The interpretation of dynamic contrast-enhanced breast MR images is predicated on the assumption of minimal voxel movement during the time course of the image acquisition. Misalignment of the dynamic image sequence as a result of movement during image acquisition can lead to potentially misleading diagnostic conclusions. In this paper a new methodology is presented for assessing the degree of in-plane (intra-slice) movement in a dynamic image sequence. The method is demonstrated on data from six subjects. The conclusion is that the method makes it possible to quantitatively qualify the accuracy of computed enhancement curves and more importantly to identify unacceptably poor registration.
|
|
| 11. |
- Qaiser, Mahmood, 1981, et al.
(author)
-
Unsupervised Segmentation of Head Tissues from Multi-modal MR Images for EEG Source Localization
- 2015
-
In: Journal of Digital Imaging. - : Springer Science and Business Media LLC. - 1618-727X .- 0897-1889. ; 28:4, s. 499-514
-
Journal article (peer-reviewed)abstract
- In this paper, we present and evaluate an automatic unsupervised segmentation method, hierarchical segmenta- tion approach (HSA)–Bayesian-based adaptive mean shift (BAMS), for use in the construction of a patient-specific head conductivity model for electroencephalography (EEG) source localization. It is based on a HSA and BAMS for segmenting the tissues from multi-modal magnetic resonance (MR) head images. The evaluation of the proposed method was done both directly in terms of segmentation accuracy and indirectly in terms of source localization accuracy. The direct evaluation was performed relative to a commonly used reference method brain extraction tool (BET)–FMRIB’s automated segmenta- tion tool (FAST) and four variants of the HSA using both synthetic data and real data from ten subjects. The synthetic data includes multiple realizations of four different noise levels and several realizations of typical noise with a 20 % bias field level. The Dice index and Hausdorff distance were used to measure the segmentation accuracy. The indirect evaluation was performed relative to the reference method BET-FAST using synthetic two-dimensional (2D) multimodal magnetic resonance (MR) data with 3 % noise and synthetic EEG (generated for a prescribed source). The source localiza- tion accuracy was determined in terms of localization error and relative error of potential. The experimental results dem- onstrate the efficacy of HSA-BAMS, its robustness to noise and the bias field, and that it provides better segmentation accuracy than the reference method and variants of the HSA. They also show that it leads to a more accurate localization accuracy than the commonly used reference method and sug- gest that it has potential as a surrogate for expert manual segmentation for the EEG source localization problem.
|
|
| 12. |
- Alipoor, Mohammad, 1983, et al.
(author)
-
A Novel Framework for repeated measurements in diffusion tensor imaging
- 2016
-
In: 3rd (ACM) Int'l Conf. on Biomedical and Bioinformatics Engineering (ICBBE 2016). - New York, NY, USA : ACM. - 9781450348249 ; Part F125793, s. 1-6
-
Conference paper (peer-reviewed)abstract
- In the context of diffusion tensor imaging (DTI), the utility of making repeated measurements in each diffusion sensitizing direction has been the subject of numerous stud-ies. One can estimate the true signal value using either the raw complex-valued data or the real-valued magnitudesignal. While conventional methods focus on the former strategy, this paper proposes a new framework for acquiring/processing repeated measurements based on the latter strategy. The aim is to enhance the DTI processing pipeline by adding a diffusion signal estimator (DSE). This permits us to exploit the knowledge of the noise distribution to estimate the true signal value in each direction. An extensive study of the proposed framework, including theoretical analysis, experiments with synthetic data, performance evaluation and comparisons is presented.Our results show that the precision of estimated diffusionparameters is dependent on the number of available samplesand the manner in which the DSE accounts for noise. Theproposed framework improves the precision in estimationof diffusion parameters given a sufficient number of uniquemeasurements. This encourages future work with rich realdatasets and downstream applications.
|
|
| 13. |
- Alipoor, Mohammad, 1983, et al.
(author)
-
K-Optimal Gradient Encoding Scheme for Fourth-Order Tensor-Based Diffusion Profile Imaging
- 2015
-
In: Biomed Research International. - : Hindawi Limited. - 2314-6133 .- 2314-6141.
-
Journal article (peer-reviewed)abstract
- The design of an optimal gradient encoding scheme (GES) is a fundamental problem in diffusion MRI. It is well studied for the case of second-order tensor imaging (Gaussian diffusion). However, it has not been investigated for the wide range of non-Gaussian diffusion models. The optimal GES is the one that minimizes the variance of the estimated parameters. Such a GES can be realized by minimizing the condition number of the design matrix (K-optimal design). In this paper, we propose a new approach to solve the K-optimal GES design problem for fourth-order tensor-based diffusion profile imaging. The problem is a nonconvex experiment design problem. Using convex relaxation, we reformulate it as a tractable semidefinite programming problem. Solving this problem leads to several theoretical properties of K-optimal design: (i) the odd moments of the K-optimal design must be zero; (ii) the even moments of the K-optimal design are proportional to the total number of measurements; (iii) the K-optimal design is not unique, in general; and (iv) the proposed method can be used to compute the K-optimal design for an arbitrary number of measurements. Our Monte Carlo simulations support the theoretical results and show that, in comparison with existing designs, the K-optimal design leads to the minimum signal deviation.
|
|
| 14. |
- Alipoor, Mohammad, 1983, et al.
(author)
-
On High Order Tensor-based Diffusivity Profile Estimation
- 2013
-
In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781457702167 ; , s. 93-96, s. 4-
-
Conference paper (peer-reviewed)abstract
- Diffusion weighted magnetic resonance imaging (dMRI) is used to measure, in vivo, the self-diffusion of water molecules in biological tissues. High order tensors (HOTs) are used to model the apparent diffusion coefficient (ADC) profile at each voxel from the dMRI data. In this paper we propose: (i) A new method for estimating HOTs from dMRI data based on weighted least squares (WLS) optimization; and (ii) A new expression for computing the fractional anisotropy from a HOT that does not suffer from singularities and spurious zeros. We also present an empirical evaluation of the proposed method relative to the two existing methods based on both synthetic and real human brain dMRI data. The results show that the proposed method yields more accurate estimation than the competing methods.
|
|
| 15. |
- Alipoor, Mohammad, 1983, et al.
(author)
-
Optimal Diffusion Tensor Imaging with Repeated Measurements
- 2013
-
In: Lecture Notes in Computer Science: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013. 16th International Conference, Nagoya, Japan, September 22-26, 2013, Proceedings, Part I. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 0302-9743 .- 1611-3349. - 9783642408106 ; 8149, s. 687-694
-
Conference paper (peer-reviewed)abstract
- Several data acquisition schemes for diffusion MRI have been proposed and explored to date for the reconstruction of the 2nd order tensor. Our main contributions in this paper are: (i) the definition of a new class of sampling schemes based on repeated measurements in every sampling point; (ii) two novel schemes belonging to this class; and (iii) a new reconstruction framework for the second scheme. We also present an evaluation, based on Monte Carlo computer simulations, of the performances of these schemes relative to known optimal sampling schemes for both 2nd and 4th order tensors. The results demonstrate that tensor estimation by the proposed sampling schemes and estimation framework is more accurate and robust.
|
|
| 16. |
- Alipoor, Mohammad, 1983, et al.
(author)
-
Optimal Experiment Design for Mono-Exponential Model Fitting: Application to Apparent Diffusion Coefficient Imaging
- 2015
-
In: BioMed Research International. - : Hindawi Limited. - 2314-6133 .- 2314-6141. ; 2015
-
Journal article (peer-reviewed)abstract
- The mono-exponential model is widely used in quantitative biomedical imaging. Notable applications include apparent diffusion coefficient (ADC) imaging and pharmacokinetics.The application of ADC imaging to the detection of malignant tissue has in turn prompted several studies concerning optimal experiment design for mono-exponential model fitting. In this paper, we propose a new experiment design method that is based on minimizing the determinant of the covariance matrix of the estimated parameters (?-optimal design). In contrast to previous methods, ?-optimal design is independent of the imaged quantities. Applying this method to ADC imaging, we demonstrate its steady performance for the whole range of input variables (imaged parameters, number of measurements, range of ?-values). Using Monte Carlo simulations we show that the ?-optimal design outperforms existing experiment design methods in terms of accuracy and precision of the estimated parameters.
|
|
| 17. |
- Alipoor, Mohammad, 1983, et al.
(author)
-
Optimal Gradient Encoding Schemes for Diffusion Tensor and Kurtosis Imaging
- 2016
-
In: IEEE transactions on Computational Imaging. - 2333-9403. ; 2:3, s. 375-391
-
Journal article (peer-reviewed)abstract
- Diffusion-derived parameters find application in characterizing pathological and developmental changes in living tissues. Robust estimation of these parameters is important because they are used for medical diagnosis. An optimal gradient encoding scheme (GES) is one that minimizes the variance of the estimated diffusion parameters. This paper proposes a method for optimal GES design for two diffusion models: high-order diffusion tensor (HODT) imaging and diffusion kurtosis imaging (DKI). In both cases, the optimal GES design problem is formulated as a D-optimal (minimum determinant) experiment design problem. Then, using convex relaxation, it is reformulated as a semidefinite programming problem. Solving these problems we show that: 1) there exists a D-optimal solution for DKI that is simultaneously D-optimal for second- and fourth-order diffusion tensor imaging (DTI); 2) the traditionally used icosahedral scheme is approximately D-optimal for DTI and DKI; 3) the proposed D-optimal design is rotation invariant; 4) the proposed method can be used to compute the optimal design ($b$ -values and directions) for an arbitrary number of measurements and shells; and 5) using the proposed method one can obtain uniform distribution of gradient encoding directions for a typical number of measurements. Importantly, these theoretical findings provide the first mathematical proof of the optimality of uniformly distributed GESs for DKI and HODT imaging. The utility of the proposed method is further supported by the evaluation results and comparisons with with existing methods.
|
|
| 18. |
|
|
| 19. |
|
|
| 20. |
- Belavy, D. L., et al.
(author)
-
Analysis of phasic and tonic electromyographic signal characteristics: Electromyographic synthesis and comparison of novel morphological and linear-envelope approaches
- 2009
-
In: Journal of Electromyography and Kinesiology. - 1873-5711 .- 1050-6411. ; 19:1, s. 10-21
-
Journal article (peer-reviewed)abstract
- The pattern of tonic and phasic components in an EMG signal reflects the underlying behaviour of the central nervous system (CNS) in controlling the musculature. One avenue for gaining a better understanding of this behaviour is to seek a quantitative characterisation of these phasic and tonic components. We propose that these signal characteristics call range between unvarying, tonic and intermittent, phasic activation through a continuum of EMG amplitude modulation. In this paper, we present two new algorithms for quantifying amplitude modulation: a linear-envelope approach, and a mathematical morphology approach. In addition we present all algorithm for synthesising EMG signals with known amplitude modulation. The efficacy of the synthesis algorithm is demonstrated using real EMG data. We present an evaluation and comparison of the two algorithms for quantifying amplitude modulation based on synthetic data generated by the proposed synthesis algorithm. The results demonstrate that the EMG synthesis parameters represent 91.9% and 96.2% of the variance of linear-envelopes extracted from lumbo-pelvic muscle EMG signals collected from subjects performing a repetitive-movement task. This depended, however, on the muscle and movement-speed considered (F = 4.02, p
|
|
| 21. |
- Ehteshami Bejnordi, B., et al.
(author)
-
Novel chromatin texture features for the classification of Pap smears
- 2013
-
In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. - : SPIE. - 1605-7422. - 9780819494504 ; 8676, s. Art. no. 867608-
-
Conference paper (peer-reviewed)abstract
- This paper presents a set of novel structural texture features for quantifying nuclear chromatin patterns in cells on a conventional Pap smear. The features are derived from an initial segmentation of the chromatin into bloblike texture primitives. The results of a comprehensive feature selection experiment, including the set of proposed structural texture features and a range of different cytology features drawn from the literature, show that two of the four top ranking features are structural texture features. They also show that a combination of structural and conventional features yields a classification performance of 0.954±0.019 (AUC±SE) for the discrimination of normal (NILM) and abnormal (LSIL and HSIL) slides. The results of a second classification experiment, using only normal-appearing cells from both normal and abnormal slides, demonstrates that a single structural texture feature measuring chromatin margination yields a classification performance of 0.815±0.019. Overall the results demonstrate the efficacy of the proposed structural approach and that it is possible to detect malignancy associated changes (MACs) in Papanicoloau stain.
|
|
| 22. |
- Engstrom, C. M., et al.
(author)
-
Quadratus lumborum asymmetry and L4 Pars injury in fast bowlers: A prospective MR study
- 2007
-
In: Medicine and Science in Sports and Exercise. - 0195-9131. ; 39:6, s. 910-917
-
Journal article (peer-reviewed)abstract
- Engstrom, C. M., D. G Walker, V. Kippers, and A. J. H. Mehnert. Quadrants Lumborum Asymmetry and L4 Pars Injury in Fast Bowlers: A Prospective MR Study. Med. Sci. Sports Exerc., Vol. 39, No. 6, pp. 910-917, 2007. Purpose: This prospective study examined the association between quadratus lumborum (QL) asymmetry and the development of symptomatic pars interarticularis lesions in the lumbar spine of adolescent cricket fast bowlers. Methods: Annual magnetic resonance imaging was used to measure QL volume asymmetry and for identifying pars lesions of the lumbar vertebrae in fast bowlers (N = 5 1) and a control group of swimmers (N = 18). Manual segmentation of axial images spanning the lumbar spine was performed to calculate percent QL asymmetry relative to the bowling- or throwing- (swimmers) arm side. Asymmetry above 100% indicated a larger QL volume on the bowling- (throwing) arm side. Results: The mean QL asymmetry in bowlers of 110.5% (SD = 12.1%) was significantly different from the 96.6% (SD = 5.0%) asymmetry in swimmers (t = 6.75, P
|
|
| 23. |
- Gal, Y., et al.
(author)
-
Denoising of Dynamic Contrast-Enhanced MR Images Using Dynamic Nonlocal Means
- 2010
-
In: IEEE Transactions on Medical Imaging. - 0278-0062. ; 29:2, s. 302-310
-
Journal article (peer-reviewed)abstract
- This paper presents a new algorithm for denoising dynamic contrast-enhanced (DCE) MR images. It is a novel variation on the nonlocal means (NLM) algorithm. The algorithm, called dynamic nonlocal means (DNLM), exploits the redundancy of information in the temporal sequence of images. Empirical evaluations of the performance of the DNLM algorithm relative to seven other denoising methods-simple Gaussian filtering, the original NLM algorithm, a trivial extension of NLM to include the temporal dimension, bilateral filtering, anisotropic diffusion filtering, wavelet adaptive multiscale products threshold, and traditional wavelet thresholding-are presented. The evaluations include quantitative evaluations using simulated data and real data (20 DCE-MRI data sets from routine clinical breast MRI examinations) as well as qualitative evaluations using the same real data (24 observers: 14 image/signal-processing specialists, 10 clinical breast MRI radiographers). The results of the quantitative evaluation using the simulated data show that the DNLM algorithm consistently yields the smallest MSE between the denoised image and its corresponding original noiseless version. The results of the quantitative evaluation using the real data provide evidence, at the alpha = 0.05 level of significance, that the DNLM algorithm yields the smallest MSE between the denoised image and its corresponding original noiseless version. The results of the qualitative evaluation provide evidence, at the alpha = 0.05 level of significance, that the DNLM algorithm performs visually better than all of the other algorithms. Collectively the qualitative and quantitative results suggest that the DNLM algorithm more effectively attenuates noise in DCE MR images than any of the other algorithms.
|
|
| 24. |
- Gal, Yaniv, et al.
(author)
-
Mutual information-based binarisation of multiple images of an object: An application in medical imaging
- 2013
-
In: IET Computer Vision. - : Institution of Engineering and Technology (IET). - 1751-9640 .- 1751-9632. ; 7:3, s. 163-169
-
Journal article (peer-reviewed)abstract
- A new method for image thresholding of two or more images that are acquired in different modalities or acquisition protocols is proposed. The method is based on measures from information theory and has no underlying free parameters nor does it require training or calibration. The method is based on finding an optimal set of global thresholds, one for each image, by maximising the mutual information above the thresholds while minimising the mutual information below the thresholds. Although some assumptions on the nature of images are made, no assumptions are made by the method on the intensity distributions or on the shape of the image histograms. The effectiveness of the method is demonstrated both on synthetic images and medical images from clinical practice. It is then compared against three other thresholding methods.
|
|
| 25. |
- Hill, A., et al.
(author)
-
Evaluating the Accuracy and Impact of Registration in Dynamic Contrast-Enhanced Breast MRI
- 2009
-
In: Concepts in Magnetic Resonance Part B: Magnetic Resonance Engineering. - 1552-5031. ; 35B:2, s. 106-120
-
Journal article (peer-reviewed)abstract
- This article presents a quantitative evaluation framework-incorporating a novel heterogeneous biomechanical model-for objectively comparing the accuracy of registration algorithms in dynamic contrast-enhanced (DCE) MRI of the breast; an evaluation of several algorithms using this framework; and several clinical examples where accurate registration significantly changes the shape of the enhancement curves associated with suspicious regions of interest (ROIs) identified by a radiologist. The experimental results demonstrate: (i) the efficacy of the evaluation framework; (ii) that a good registration algorithm can accurately recover the shapes of voxel enhancement curves from breast DCE-MRI data containing motion; (iii) that motion of as little as I mm can significantly change the shape of the mean enhancement curve for an ROI; and (iv) that accurate registration can significantly change the shape of enhancement curves estimated for small and large ROIs even when there is little or no visible evidence of motion. This suggests that all DCE-MRI breast data should be spatially aligned using a nonrigid registration algorithm before the analysis of contrast enhancement. (C) 2009 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 3513: 106-120, 2009
|
|
| 26. |
- Jackway, Paul, et al.
(author)
-
Chromatin segmentation
- 2009
-
Patent (other academic/artistic)abstract
- A method of segmenting chromatin particles in a nucleus of a cell by locating regional minima in an image, computing a zone of influence (ZOI) around each regional minimum, and segmenting a single chromatin blob within each ZOI using a region growing procedure. The method can be used as the basis of a method of qualitatively characterizing the distribution of nuclear chromatin by computing features for individual chromatin particles. Chromatin features can be synthesized from the features of individual particles and particle features can be synthesized into nucleus features and slide features. The method is useful for detecting malignancy associated changes and changes during neoplasia. The method may also be used more generally to assess chromatin patterns in living cells during the cell life cycle. This makes it possible to measure alternations in the evolving patterns that result from pathological or environmental influences.
|
|
| 27. |
- Jackway, Paul, et al.
(author)
-
Chromatin segmentation
- 2007
-
Patent (other academic/artistic)abstract
- A method of segmenting chromatin particles in a nucleus of a cell by locating regional minima in an image, computing a zone of influence (ZOI) around each regional minimum, and segmenting a single chromatin blob within each ZOI using a region growing procedure. The method can be used as the basis of a method of qualitatively characterizing the distribution of nuclear chromatin by computing features for individual chromatin particles. Chromatin features can be synthesized from the features of individual particles and particle features can be synthesized into nucleus features and slide features. The method is useful for detecting malignancy associated changes and changes during neoplasia. The method may also be used more generally to assess chromatin patterns in living cells during the cell life cycle. This makes it possible to measure alternations in the evolving patterns that result from pathological or environmental influences.
|
|
| 28. |
- Lindblad, Joakim, et al.
(author)
-
Optimizing optics and imaging for pattern recognition based screening tasks
- 2014
-
In: Proceedings - International Conference on Pattern Recognition. - : IEEE Computer Society. - 1051-4651. - 9781479952083 ; , s. 3333-3338
-
Conference paper (peer-reviewed)abstract
- We present a method for simulating lower quality images starting from higher quality ones, based on acquired image pairs from different optical setups. The method does not require estimates of point (or line) spread functions of the system, but utilizes the relative transfer function derived from images of real specimen of interest in the observed application. Thanks to the use of a larger number of real specimen, excellent stability and robustness of the method is achieved. The intended use is exploring the influence of image quality on features and classification accuracy in pattern recognition based screening tasks. Visual evaluation of the obtained images strongly confirms usefulness of the method. The approach is quantitatively evaluated by observing stability of feature values, proven useful for PAP-smear classification, between synthetic and real images from seven different microscope setups. The evaluation shows that features from the synthetically generated lower resolution images are as similar to features from real images at that resolution, as features from two different images of the same specimen, taken at the same low resolution, are to each other.
|
|
| 29. |
- Malmberg, Filip, et al.
(author)
-
Relaxed Image Foresting Transforms for Interactive Volume Image Segmentation
- 2010
-
In: MEDICAL IMAGING 2010. - : SPIE. - 9780819480248 ; 7623
-
Conference paper (peer-reviewed)abstract
- The image Foresting (IFT) is a framework for image partitioning, commonly used for interactive segmentation. Given an image where a subset of the image elements (seed-points) have been assigned correct segmentation labels, the IFT completes the labeling by computing minimal cost paths from all image elements to the seed-points. Each image element is then given the same label as the closest seed-point. Here, we propose the relaxed IFT (RIFT). This modified version of the IFT features an additional parameter to control the smoothness of the segmentation boundary. The RIFT yields more intuitive segmentation results in the presence of noise and weak edges, while maintaining a low computational complexity. We show an application of the method to the refinement of manual segmentations of a thoracolumbar muscle in magnetic resonance images. The performed study shows that the refined segmentations are qualitatively similar to the manual segmentations, while intra-user variations are reduced by more than 50%.
|
|
| 30. |
- McClymont, Darryl, et al.
(author)
-
A novel method for automatic extraction of apparent diffusion coefficients in breast MRI
- 2011
-
In: Proc. Intl. Soc. Mag. Reson. Med. 19 (2011). ; , s. 2014-
-
Conference paper (peer-reviewed)abstract
- Diffusion weighted (DW) MRI—and in particular the apparent diffusion coefficient (ADC)—shows potential for improving the characterization and classification of enhancing breast lesions identified using dynamic contrast-enhanced (DCE) MRI. Nevertheless, to date there does not exist a well defined and objective method for computing a representative ADC value for such lesions. Typically an average ADC is computed for a manually selected region of interest (ROI) [1]. This is problematic for two reasons. Firstly the choice of ROI is subjective. Differences in ROI selection between individuals, as well as the reproducibility of selection for a given individual, can lead to variation in the mean ADC. In addition ROIs are often defined to be circular or elliptical which imposes an arbitrary geometry on the ROI [2]. Secondly, given the heterogeneity in breast lesions, an ensemble average of ADC may not provide a truly representative value. It is assumed that a representative ADC will be present in the area of neovascularisation, as indicated by rapid contrast enhancement. In order to improve the objectivity, reproducibility and efficiency of representative ADC computation, we propose an automated method based on the selection of hypo-intense areas on the ADC map corresponding to regions of greatest initial contrast enhancement identified in the DCE-MRI data. We also present an evaluation of the method using routine clinical data.
|
|
| 31. |
- McClymont, Darryl, et al.
(author)
-
Automated selection of hypointense regions in diffusion-weighted breast MRI
- 2012
-
In: Proc. Intl. Soc. Mag. Reson. Med. 20 (2012).
-
Conference paper (peer-reviewed)abstract
- Recent research suggests that diffusion-weighted (DW) MRI, and in particular the apparent diffusion coefficient (ADC), can be used to improve the sensitivity and specificity of dynamic contrast-enhanced (DCE) MRI for the detection of breast cancer. However, to date the methods proposed for determining a representative ADC value for a suspicious lesion are highly varied. One approach is to compute the mean ADC value over the entire lesion to obtain a representative ADC value. Another is to compute the mean ADC value within one or more regions of interest (ROIs) defined on the suspicious lesion. The earliest examples of this approach involve manually defining ROIs of hypointensity to be as large as possible, but constrained within the lesion, and such that areas of necrosis are avoided in large lesions. More recent examples of this approach involve placing one or more smaller ROIs of hypointensity within a suspicious lesion and computing, for example, the global minimum [1] or mean [2]. This latter approach appears to provide better discrimination between benign and malignant lesions. Nevertheless to date there does not exist a well-defined and objective method for defining these ROIs. The problem is complicated by the typically low signal-to-noise ratio in the DW images. We propose an automated method based on the converging squares algorithm [3], which is a multiscale minimum finding technique with inherent robustness to noise. We also present an evaluation of the method, using routine clinical data, for computing a representative ADC value for discriminating benign and malignant lesions. The method is also compared to ensemble averaging of ADC values over the entire lesion and the selection of the global minimum ADC value.
|
|
| 32. |
- McClymont, D., et al.
(author)
-
Fully Automatic Lesion Segmentation in Breast MRI Using Mean-Shift and Graph-Cuts on a Region Adjacency Graph
- 2014
-
In: Journal of Magnetic Resonance Imaging. - : Wiley. - 1053-1807 .- 1522-2586. ; 39:4, s. 795-804
-
Journal article (peer-reviewed)abstract
- PurposeTo present and evaluate a fully automatic method for segmentation (i.e., detection and delineation) of suspicious tissue in breast MRI. Materials and MethodsThe method, based on mean-shift clustering and graph-cuts on a region adjacency graph, was developed and its parameters tuned using multimodal (T1, T2, DCE-MRI) clinical breast MRI data from 35 subjects (training data). It was then tested using two data sets. Test set 1 comprises data for 85 subjects (93 lesions) acquired using the same protocol and scanner system used to acquire the training data. Test set 2 comprises data for eight subjects (nine lesions) acquired using a similar protocol but a different vendor's scanner system. Each lesion was manually delineated in three-dimensions by an experienced breast radiographer to establish segmentation ground truth. The regions of interest identified by the method were compared with the ground truth and the detection and delineation accuracies quantitatively evaluated. ResultsOne hundred percent of the lesions were detected with a mean of 4.5 1.2 false positives per subject. This false-positive rate is nearly 50% better than previously reported for a fully automatic breast lesion detection system. The median Dice coefficient for Test set 1 was 0.76 (interquartile range, 0.17), and 0.75 (interquartile range, 0.16) for Test set 2. ConclusionThe results demonstrate the efficacy and accuracy of the proposed method as well as its potential for direct application across different MRI systems. It is (to the authors' knowledge) the first fully automatic method for breast lesion detection and delineation in breast MRI. J. Magn. Reson. Imaging 2014;39:795-804. (c) 2013 Wiley Periodicals, Inc.
|
|
| 33. |
- McClymont, Darryl, et al.
(author)
-
Improving the discrimination of benign and malignant breast MRI lesions using the apparent diffusion coefficient
- 2010
-
In: Proc. 2010 International Conference on Digital Image Computing: Techniques and Applications (DICTA). - 9781424488162 ; , s. 569 - 574
-
Conference paper (peer-reviewed)abstract
- This paper presents an investigation of the apparent diffusion coefficient (ADC) for improving the discrimination of benign and malignant lesions in breast magnetic resonance imaging (MRI). In particular a method is presented for automatically selecting hyper intense tumour voxels in dynamic contrast enhanced (DCE) MRI data and evaluating their average ADC in the corresponding diffusion-weighted (DW) MRI data. The method was applied to ten breast MRI datasets obtained from routine clinical practice. The results demonstrate that the combination of the relative signal increase (DCE-MRI) with the apparent diffusion coefficient (DW-MRI) leads to better discrimination than with either feature alone. The results also suggest that it is important to acquire the DW-MRI data in a consistent fashion, i.e. either before or after the acquisition of the DCE-MRI data.
|
|
| 34. |
|
|
| 35. |
- Mehnert, Andrew, 1967, et al.
(author)
-
A Structural texture approach for characterising malignancy associated changes in pap smears based on mean-shift and the watershed transform
- 2014
-
In: Proceedings - International Conference on Pattern Recognition. - : IEEE Computer Society. - 1051-4651. - 9781479952083 ; , s. 1189-1193
-
Conference paper (peer-reviewed)abstract
- This paper presents a novel structural approach to quantitatively characterising nuclear chromatin texture in light microscope images of Pap smears. The approach is based on segmenting the chromatin into blob-like primitives and characterising their properties and arrangement. The segmentation approach makes use of multiple focal planes. It comprises two basic steps: (i) mean-shift filtering in the feature space formed by concatenating pixel spatial coordinates and intensity values centred around the best all-in-focus plane, and (ii) hierarchical marker-based watershed segmentation. The paper also presents an empirical evaluation of the approach based on the classification of 43 routine clinical Pap smears. Two variants of the approach were compared to a reference approach (employing extended depth-of-field rather than mean-shift) in a feature selection/classification experiment, involving 138 segmentation-based features, for discriminating normal and abnormal slides. The results demonstrate improved performance over the reference approach. The results of a second feature selection/classification experiment, including additional classes of features from the literature, show that a combination of the proposed structural and conventional features yields a classification performance of 0.919±0.015 (AUC ± Std. Dev.). Overall the results demonstrate the efficacy of the proposed structural approach and confirm that it is indeed possible to detect malignancy associated changes (MACs) in conventional Papanicolaou stain.
|
|
| 36. |
- Mehnert, Andrew, 1967, et al.
(author)
-
An improved seeded region growing algorithm
- 1997
-
In: Pattern Recognition Letters. - 0167-8655. ; 18:10, s. 1065-1071
-
Journal article (peer-reviewed)abstract
- Recently Adams and Bischof (1994) proposed a novel region growing algorithm for segmenting intensity images. The inputs to the algorithm are the intensity image and a set of seeds - individual points or connected components - that identify the individual regions to be segmented. The algorithm grows these seed regions until all of the image pixels have been assimilated. Unfortunately the algorithm is inherently dependent on the order of pixel processing. This means, for example, that raster order processing and anti-raster order processing do not, in general, lead to the same tessellation. In this paper we propose an improved seeded region growing algorithm that retains the advantages of the Adams and Bischof algorithm fast execution, robust segmentation, and no tuning parameters - but is pixel order independent. (C) 1997 Elsevier Science B.V.
|
|
| 37. |
- Mehnert, Andrew, 1967, et al.
(author)
-
Folding induced self-dual filters
- 2000
-
In: Mathematical Morphology and its Applications to Image and Signal Processing. - 9780792378624 ; , s. 99-108
-
Conference paper (peer-reviewed)abstract
- In this paper we present a method for constructing self-dual grey-scale image operators from arbitrary morphological operators defined on what we call fold-space. We call this class of self-dual operators folding induced self-dual filters (FISFs). We show examples of their application to noise filtering.
|
|
| 38. |
- Mehnert, Andrew, 1967, et al.
(author)
-
On computing the exact Euclidean distance transform on rectangular and hexagonal grids
- 1999
-
In: Journal of Mathematical Imaging and Vision. - 1573-7683 .- 0924-9907. ; 11:3, s. 223-230
-
Journal article (peer-reviewed)abstract
- In this paper we prove an equivalence relation between the distance transform of a binary image, where the underlying distance is based on a positive definite quadratic form, and the erosion of its characteristic function by an elliptic poweroid structuring element. The algorithms devised by Shih and Mitchell [18] and Huang and Mitchell [7], for calculating the exact Euclidean distance transform (EDT) of a binary digital image manifested on a square grid, are particular cases of this result. The former algorithm uses erosion by a circular cone to calculate the EDT whilst the latter uses erosion by an elliptic paraboloid (which allows for pixel aspect ratio correction) to calculate the square of the EDT. Huang and Mitchell's algorithm [7] is arguably the better of the two because: (i) the structuring element can be decomposed into a sequence of dilations by 3 x 3 structuring elements (a similar decomposition is not possible for the circular cone) thus reducing the complexity of the erosion, and (ii) the algorithm only requires integer arithmetic (it produces squared distance). The algorithm is amenable to both hardware implementation using a pipeline architecture and efficient implementation on serial machines. Unfortunately the algorithm does not directly transpose to, nor has a corresponding analogue on, the hexagonal grid (the same is also true for Shih and Mitchell's algorithm [7]). In this paper, however, we show that if the hexagonal grid image is embedded in a rectangular grid then Huang and Mitchell's algorithm [7] can be applied, with aspect ratio correction, to obtain the exact EDT on the hexagonal grid.
|
|
| 39. |
- Mehnert, Andrew, 1967, et al.
(author)
-
Two non-linear parametric models of contrast enhancement for DCE-MRI of the breast amenable to fitting using linear least squares
- 2010
-
In: Proc. 2010 International Conference on Digital Image Computing: Techniques and Applications (DICTA). - IEEE Computer Society, Los Alamitos, CA, USA : IEEE Computer Society. - 9781424488162 ; , s. 611-616
-
Conference paper (peer-reviewed)abstract
- This paper proffers two non-linear empirical parametric models - linear slope and Ricker - for use in characterising contrast enhancement in dynamic contrast enhanced (DCE) MRI. The advantage of these models over existing empirical parametric and pharmacokinetic models is that they can be fitted using linear least squares (LS). This means that fitting is quick, there is no need to specify initial parameter estimates, and there are no convergence issues. Furthermore the LS fit can itself be used to provide initial parameter estimates for a subsequent NLS fit (self-starting models). The results of an empirical evaluation of the goodness of fit (GoF) of these two models, measured in terms of both MSE and R2, relative to a two-compartment pharmacokinetic model and the Hayton model are also presented. The GoF was evaluated using both routine clinical breast MRI data and a single high temporal resolution breast MRI data set. The results demonstrate that the linear slope model fits the routine clinical data better than any of the other models and that the two parameter self-starting Ricker model fits the data nearly as well as the three parameter Hayton model. This is also demonstrated by the results for the high temporal data and for several temporally sub-sampled versions of this data.
|
|
| 40. |
- Mehnert, Andrew, 1967, et al.
(author)
-
Two non-linear parametric models of enhancement for breast DCE-MRI that can be fitted using linear least squares
- 2011
-
In: Proc. Intl. Soc. Mag. Reson. Med. 19 (2011). ; , s. 2627-
-
Conference paper (peer-reviewed)abstract
- The interpretation of dynamic contrast enhanced (DCE) MR images of the breast is predicated on the assessment of tissue enhancement kinetics. Both pharmacokinetic (PK) and empirical parametric (EP) models have been developed to quantify this change in enhancement. The former aim to measure physiologically meaningful parameters while the latter seek to measure the shape of the enhancement curve. Given that different PK models can yield markedly different estimates of the same physiological parameter (because of model assumptions) and that such models need to be fitted using non-linear least squares (NLS) which is in itself problematic (need to specify starting values, convergence issues), EP models remain of interest. Herein we propose two such models—linear-slope [1] and Ricker [2]—which have the advantage that they can be fitted using linear least squares (LS) meaning that fitting is quick and that there is no need to specify initial parameter estimates. Furthermore, if desired, the LS fit can be used to provide parameter estimates for a subsequent NLS fit. The results of an empirical evaluation of the goodness-of-fit (GoF) of these two models relative to the pharmacokinetically-inspired Hayton model [2], and the simplified gamma-variate model [4] are also presented.
|
|
| 41. |
|
|
| 42. |
- Moshavegh, Ramin, et al.
(author)
-
Automated segmentation of free-lying cell nuclei in Pap smears for malignancy-associated change analysis
- 2012
-
In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781424441198 ; , s. 5372-5375
-
Conference paper (peer-reviewed)abstract
- This paper presents an automated algorithm for robustly detecting and segmenting free-lying cell nuclei in bright-field microscope images of Pap smears. This is an essential initial step in the development of an automated screening system for cervical cancer based on malignancy associated change (MAC) analysis. The proposed segmentation algorithm makes use of gray-scale annular closings to identify free-lying nuclei-like objects together with marker-based watershed segmentation to accurately delineate the nuclear boundaries. The algorithm also employs artifact rejection based on size, shape, and granularity to ensure only the nuclei of intermediate squamous epithelial cells are retained. An evaluation of the performance of the algorithm relative to expert manual segmentation of 33 fields-of-view from 11 Pap smear slides is also presented. The results show that the sensitivity and specificity of nucleus detection is 94.71% and 85.30% respectively, and that the accuracy of segmentation, measured using the Dice coefficient, of the detected nuclei is 97.30±1.3%.
|
|
| 43. |
- Qaiser, Mahmood, 1981, et al.
(author)
-
A Comparative Study of Automated Segmentation Methods for Use in a Microwave Tomography System for Imaging Intracerebral Hemorrhage in Stroke Patients
- 2015
-
In: Journal of Electromagnetic Analysis and Applications. - : Scientific Research Publishing, Inc.. - 1942-0749 .- 1942-0730. ; 7, s. 152-167
-
Journal article (peer-reviewed)abstract
- Microwave technology offers the possibility for pre-hospital stroke detection as we have pre- viously demonstrated using non-imaging diagnostics. The focus in this paper is on image-based diagnostics wherein the technical and computational complexities of image reconstruction are a challenge for clinical realization. Herein we investigate whether information about a patient’s brain anatomy obtained prior to a stroke event can be used to facilitate image-based stroke diag- nostics. A priori information can be obtained by segmenting the patient’s head tissues from mag- netic resonance images. Expert manual segmentation is presently the gold standard, but it is labo- rious and subjective. A fully automatic method is thus desirable. This paper presents an evaluation of several such methods using both synthetic magnetic resonance imaging (MRI) data and real da- ta from four healthy subjects. The segmentation was performed on the full 3D MRI data, whereas the electromagnetic evaluation was performed using a 2D slice. The methods were evaluated in terms of: i) tissue classification accuracy over all tissues with respect to ground truth, ii) the accu- racy of the simulated electromagnetic wave propagation through the head, and iii) the accuracy of the image reconstruction of the hemorrhage. The segmentation accuracy was measured in terms of the degree of overlap (Dice score) with the ground truth. The electromagnetic simulation accu- racy was measured in terms of signal deviation relative to the simulation based on the ground truth. Finally, the image reconstruction accuracy was measured in terms of the Dice score, relative error of dielectric properties, and visual comparison between the true and reconstructed intrace- rebral hemorrhage. The results show that accurate segmentation of tissues (Dice score = 0.97) from the MRI data can lead to accurate image reconstruction (relative error = 0.24) for the intra- cerebral hemorrhage in the subject’s brain. They also suggest that accurate automated segmenta- tion can be used as a surrogate for manual segmentation and can facilitate the rapid diagnosis of intracerebral hemorrhage in stroke patients using a microwave imaging system.
|
|
| 44. |
- Qaiser, Mahmood, 1981, et al.
(author)
-
A novel Bayesian approach to adaptive mean shift segmentation of brain images
- 2012
-
In: Proceedings - IEEE Symposium on Computer-Based Medical Systems. - 1063-7125. - 9781467320511
-
Conference paper (peer-reviewed)abstract
- We present a novel adaptive mean shift (AMS) algorithm for the segmentation of tissues in magnetic resonance (MR) brain images. In particular we introduce a novel Bayesian approach for the estimation of the adaptive kernel bandwidth and investigate its impact on segmentation accuracy. We studied the three class problem where the brain tissues are segmented into white matter, gray matter and cerebrospinal fluid. The segmentation experiments were performed on both multi-modal simulated and real patient T1-weighted MR volumes with different noise characteristics and spatial inhomogeneities. The performance of the algorithm was evaluated relative to several competing methods using real and synthetic data. Our results demonstrate the efficacy of the proposed algorithm and that it can outperform competing methods, especially when the noise and spatial intensity inhomogeneities are high.
|
|
| 45. |
|
|
| 46. |
- Tohnak, S., et al.
(author)
-
Dental CT metal artefact reduction based on sequential substitution
- 2011
-
In: Dentomaxillofacial Radiology. - : British Institute of Radiology. - 0250-832X .- 1476-542X. ; 40:3, s. 184-190
-
Journal article (peer-reviewed)abstract
- Objective: Metal artefacts can seriously degrade the visual quality and interpretability of dental CT images. Existing image processing algorithms for metal artefact reduction (MAR) are either too computationally expensive to be used in clinical scanners or effective only in correcting mild artefacts. The aim of the present study was to investigate whether it is possible to improve the efficacy of the computationally efficient projection-correction approach to MAR by exploiting the spatial dependency or autocorrelation between adjacent CT slices. Methods: A new projection-correction algorithm [MAR by sequential substitution (MARSS)] was developed based on the idea that the corrupted portions of the projection data can be substituted with the corresponding portions from an unaffected adjacent slice. The performance of MARSS was evaluated relative to the projection-correction method of Watzke and Kalendar using a two-alternative forced choice (2AFC) visual trial involving 20 observers and 20 clinical CT data sets.(16) Results: The Cochran Q test revealed no significant difference in the responses across all observers. The data were then pooled and analysed using a one-tailed exact binomial test. This revealed that the proportion of responses in favour of MARSS was significant (P
|
|
| 47. |
- Tohnak, Sirilawan, et al.
(author)
-
Dental identification system based on unwrapped CT images
- 2009
-
In: Proc. 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - 9781424432967 ; , s. 3549 - 3552
-
Conference paper (peer-reviewed)abstract
- Dental comparison of postmortem (PM) and ante-mortem (AM) radiographs provides one of the best avenues for the forensic identification of human remains. Nevertheless conventional dental comparison is labor-intensive, subjective, and has several inherent drawbacks. This paper presents a semi-automated image analysis system designed to assist the forensic dentist with the task of identifying human remains. This system overcomes the drawbacks of conventional dental comparison because it is based on the comparison of radiograph-like images reconstructed from PM computed tomography (CT) data with AM digitized conventional radiographs. The efficacy of the system is demonstrated using 4 dental CT data sets and 32 digitized bitewing radiographs obtained from routine clinical practice.
|
|
| 48. |
- Tohnak, S., et al.
(author)
-
Synthesizing dental radiographs for human identification
- 2007
-
In: Journal of Dental Research. - 0022-0345 .- 1544-0591. ; 86:11, s. 1057-1062
-
Journal article (peer-reviewed)abstract
- The task of identifying human remains based on dental comparisons of post mortem (PM) and ante mortem (AM) radiographs is labor-intensive, subjective, and has several drawbacks, including: inherently poor image quality, difficulty matching the viewing angles in PM radiographs to those taken AM, and the fact that the state of the dental remains may entirely preclude the possibility of obtaining certain types of radiographs PM. The aim of the present study was to investigate the feasibility of using radiograph-like images reconstructed from PM x-ray computed tomography (CT) data to overcome the shortcomings of conventional radiographic comparison. Algorithms for computer synthesis of panoramic, periapical, and bitewing images are presented. The algorithms were evaluated with data from clinical examinations of two persons. The results demonstrate the efficacy of the CT-based approach and that, in comparison with conventional radiographs, the synthesized images exhibit minimal geometric distortion, reduced blurring, and reduced superimposition of oral structures.
|
|
| 49. |
- Tohnak, Sirilawan, et al.
(author)
-
Synthesizing panoramic radiographs by unwrapping dental CT data
- 2006
-
In: Proc. 2006 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - 1424400325 ; , s. 3329 - 3332
-
Conference paper (peer-reviewed)abstract
- A method for synthesizing panoramic radiographs from dental CT data is presented. The method is based on the principles of panoramic radiography with a continuously-moving rotation center. The method computes discrete pixel sums through the CT data along normals to the medial axis of the dental arch. Compared to a conventional panoramic radiograph, the method produces less geometric distortion, less blurring, and less superimposition of other structures. The method is particularly suited to forensic identification of human remains in cases where the state of degradation precludes the possibility of obtaining a conventional panoramic radiograph
|
|
| 50. |
- Vidholm, Erik, et al.
(author)
-
Hardware accelerated visualization of parametrically mapped dynamic breast MRI data
- 2007
-
In: Proceedings of MICCAI workshop: Interaction in Medical Image Analysis and Visualization. - 978 0 643 09521 2 - 9780643095212 ; , s. 33-40, s. 33-40
-
Conference paper (peer-reviewed)abstract
- We present a new approach to visualising parametric vol-umes obtained in voxel-wise model fitting of dynamic contrast-enhanced(DCE) MRI data of the breast. The visualisation makes use of hardware-accelerated rendering to obtain an interactive, 3D colour-correct maxi-mum intensity projection (MIP). The method has been realised in soft-ware that permits the user to not only interactively visualise the paramet-ric volume but also to delineate 3D regions of interest using a 2D slice-wise interface. Experimental results, based on 14 DCE-MRI data setsfrom routine clinical practice, show that using the visualisation/tracingtool a medically qualified operator can achieve the same sensitivity forthe detection of malignancy as a radiologist using conventional manualinterpretation, but with better specificity. The results demonstrate thatthe visualisation methodology/software has potential as a tool for assist-ing the radiologist with the task of interpreting 4D DCE-MRI data inthe routine clinical setting.
|
|
