1. |
- Azar, Jimmy, et al.
(author)
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Automated Classification of Glandular Tissue by Statistical Proximity Sampling
- 2015
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In: International Journal of Biomedical Imaging. - : Hindawi Limited. - 1687-4188 .- 1687-4196.
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Journal article (peer-reviewed)abstract
- Due to the complexity of biological tissue and variations in staining procedures, features that are based on the explicit extraction of properties from subglandular structures in tissue images may have difficulty generalizing well over an unrestricted set of images and staining variations. We circumvent this problem by an implicit representation that is both robust and highly descriptive, especially when combined with a multiple instance learning approach to image classification. The new feature method is able to describe tissue architecture based on glandular structure. It is based on statistically representing the relative distribution of tissue components around lumen regions, while preserving spatial and quantitative information, as a basis for diagnosing and analyzing different areas within an image. We demonstrate the efficacy of the method in extracting discriminative features for obtaining high classification rates for tubular formation in both healthy and cancerous tissue, which is an important component in Gleason and tubule-based Elston grading. The proposed method may be used for glandular classification, also in other tissue types, in addition to general applicability as a region-based feature descriptor in image analysis where the image represents a bag with a certain label (or grade) and the region-based feature vectors represent instances.
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2. |
- Eklund, Anders, et al.
(author)
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Fast Random Permutation Tests Enable Objective Evaluation of Methods for Single Subject fMRI Analysis
- 2011
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In: International Journal of Biomedical Imaging. - : Hindawi Publishing Corporation. - 1687-4188 .- 1687-4196.
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Journal article (peer-reviewed)abstract
- Parametric statistical methods, such as Z-, t-, and F-values are traditionally employed in functional magnetic resonance imaging (fMRI) for identifying areas in the brain that are active with a certain degree of statistical significance. These parametric methods, however, have two major drawbacks. First, it is assumed that the observed data are Gaussian distributed and independent; assumptions that generally are not valid for fMRI data. Second, the statistical test distribution can be derived theoretically only for very simple linear detection statistics. With non-parametric statistical methods, the two limitations described above can be overcome. The major drawback of non-parametric methods is the computational burden with processing times ranging from hours to days, which so far have made them impractical for routine use in single subject fMRI analysis. In this work, it is shown how the computational power of cost-efficient Graphics Processing Units (GPUs) can be used to speed up random permutation tests. A test with 10 000 permutations takes less than a minute, making statistical analysis of advanced detection methods in fMRI practically feasible. To exemplify the permutation based approach, brain activity maps generated by the General Linear Model (GLM) and Canonical Correlation Analysis (CCA) are compared at the same significance level. During the development of the routines and writing of the paper, 3-4 years of processing time has been saved by using the GPU.
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3. |
- Eklund, Anders, et al.
(author)
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True 4D Image Denoising on the GPU
- 2011
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In: International Journal of Biomedical Imaging. - : Hindawi Publishing Corporation. - 1687-4188 .- 1687-4196. ; 2011
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Journal article (peer-reviewed)abstract
- The use of image denoising techniques is an important part of many medical imaging applications. One common application isto improve the image quality of low-dose, i.e. noisy, computed tomography (CT) data. The medical imaging domain has seen atremendous development during the last decades. It is now possible to collect time resolved volumes, i.e. 4D data, with a number ofmodalities (e.g. ultrasound (US), CT, magnetic resonance imaging (MRI)). While 3D image denoising previously has been appliedto several volumes independently, there has not been much work done on true 4D image denoising, where the algorithm considersseveral volumes at the same time (and not a single volume at a time). By using all the dimensions, it is for example possibleto remove some of the time varying reconstruction artefacts that exist in CT volumes. The problem with 4D image denoising,compared to 2D and 3D denoising, is that the computational complexity increases exponentially.In this paper we describe a novel algorithm for true 4D image denoising, based on local adaptive filtering, and how to implementit on the graphics processing unit (GPU). The algorithm was applied to a 4D CT heart dataset of the resolution 512 x 512 x 445 x 20.The result is that the GPU can complete the denoising in about 25 minutes if spatial filtering is used and in about 8 minutes if FFTbased filtering is used. The CPU implementation requires several days of processing time for spatial filtering and about 50 minutesfor FFT based filtering. Fast spatial filtering makes it possible to apply the denoising algorithm to larger datasets (compared to ifFFT based filtering is used). The short processing time increases the clinical value of true 4D image denoising significantly.
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4. |
- Fhager, Andreas, 1976, et al.
(author)
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Antenna Modeling and Reconstruction Accuracy of Time Domain-Based Image Reconstruction in Microwave Tomography
- 2013
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In: International Journal of Biomedical Imaging. - : Hindawi Limited. - 1687-4188 .- 1687-4196. ; 2013
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Journal article (peer-reviewed)abstract
- Nonlinear microwave imaging heavily relies on an accurate numerical electromagneticmodel of the antenna system. The model is used to simulate scatteringdata that is compared to its measured counterpart in order to reconstruct the image. In this paper an antenna system immersed in water is used to image differentcanonical objects in order to investigate the implication of modeling errors on thefinal reconstruction using a time domain-based iterative inverse reconstruction algorithmand three-dimensional FDTD modeling. With the test objects immersedin a background of air and tap water, respectively, we have studied the impact ofantenna modeling errors, errors in the modeling of the background media, and madea comparison with a two-dimensional version of the algorithm. In conclusion evensmall modeling errors in the antennas can significantly alter the reconstructed image. Since the image reconstruction procedure is highly nonlinear general conclusions arevery difficult to make. In our case it means that with the antenna system immersedin water and using our present FDTD-based electromagnetic model the imagingresults are improved if refraining from modeling the water-wall-air interface andinstead just use a homogeneous background of water in the model.
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5. |
- Hamid Muhammed, Hamed, et al.
(author)
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Automatic characterization of the physiological condition of the carotid artery in 2D ultrasound image sequences using spatiotemporal and spatiospectral 2D maps
- 2014
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In: International Journal of Biomedical Imaging. - : Hindawi Limited. - 1687-4188 .- 1687-4196. ; 2014
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Journal article (peer-reviewed)abstract
- A novel method for characterizing and visualizing the progression of waves along the walls of the carotid artery is presented. The new approach is noninvasive and able to simultaneously capture the spatial and the temporal propagation of wavy patterns along the walls of the carotid artery in a completely automated manner. Spatiotemporal and spatiospectral 2D maps describing these patterns (in both the spatial and the frequency domains, resp.) were generated and analyzed by visual inspection as well as automatic feature extraction and classification. Three categories of cases were considered: pathological elderly, healthy elderly, and healthy young cases. Automatic differentiation, between cases of these three categories, was achieved with a sensitivity of 97.1% and a specificity of 74.5%. Two features were proposed and computed to measure the homogeneity of the spatiospectral 2D map which presents the spectral characteristics of the carotid artery wall's wavy motion pattern which are related to the physical, mechanical (e.g., elasticity), and physiological properties and conditions along the artery. These results are promising and confirm the potential of the proposed method in providing useful information which can help in revealing the physiological condition of the cardiovascular system.
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6. |
- Hänni, Mari, et al.
(author)
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Postangioplasty restenosis followed with magnetic resonance imaging in an atherosclerotic rabbit model
- 2012
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In: International Journal of Biomedical Imaging. - : Hindawi Publishing Corporation. - 1687-4188 .- 1687-4196. ; 2012, s. 747264-
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Journal article (peer-reviewed)abstract
- Rationale and Objectives. Testing a quantitative, noninvasive method to assess postangioplasty vessel wall changes in an animal model. Material and Methods. Six New Zealand white rabbits were subjected to atherosclerotic injury, including cholesterol-enriched diet, deendothelialization, and percutaneous transluminal angioplasty (PTA) in the distal part of abdominal aorta (four weeks after deendothelialization). The animals were examined with a 1.5T MRI scanner at three times as follows: baseline (six weeks after diet start and two days after PTA) and four weeks and 10 weeks after-PTA. Inflow angiosequence (M2DI) and proton-density-weighted sequence (PDW) were performed to examine the aorta with axial slices. To identify the inner and outer vessel wall boundaries, a dynamic contour algorithm (Gradient Vector Flow Snakes) was applied to the images, followed by calculation of the vessel wall dimensions. The results were compared with histopathological analysis. Results. The wall thickness in the lesion was significantly higher than in the control region at 4 and 10 weeks, reflecting induction of experimentally created after-angioplasty lesion. At baseline, no significant difference between the two regions was present. Conclusions. It is possible to follow the development of vessel wall changes after-PTA with MRI in this rabbit model.
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7. |
- Lui, Hoi-Shun, 1980, et al.
(author)
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On the Forward Scattering of Microwave Breast Imaging
- 2012
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In: International Journal of Biomedical Imaging. - : Hindawi Limited. - 1687-4188 .- 1687-4196. ; 2012, s. 582037-
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Journal article (peer-reviewed)abstract
- Microwave imaging for breast cancer detection has been of significant interest for the last two decades. Recent studies focus on solving the imaging problem using an inverse scattering approach. Efforts have mainly been focused on the development of the inverse scattering algorithms, experimental setup, antenna design and clinical trials. However, the success of microwave breast imaging also heavily relies on the quality of the forward data such that the tumor inside the breast volume is well illuminated. In this work, a numerical study of the forward scattering data is conducted. The scattering behavior of simple breast models under different polarization states and aspect angles of illumination are considered. Numerical results have demonstrated that better data contrast could be obtained when the breast volume is illuminated using cross-polarized components in linear polarization basis or the copolarized components in the circular polarization basis.
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8. |
- Oppedal, K, et al.
(author)
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Classifying dementia using local binary patterns from different regions in magnetic resonance images
- 2015
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In: International journal of biomedical imaging. - : Hindawi Limited. - 1687-4188 .- 1687-4196. ; 2015, s. 572567-
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Journal article (peer-reviewed)abstract
- Dementia is an evolving challenge in society, and no disease-modifying treatment exists. Diagnosis can be demanding and MR imaging may aid as a noninvasive method to increase prediction accuracy. We explored the use of 2D local binary pattern (LBP) extracted from FLAIR and T1 MR images of the brain combined with a Random Forest classifier in an attempt to discern patients with Alzheimer's disease (AD), Lewy body dementia (LBD), and normal controls (NC). Analysis was conducted in areas with white matter lesions (WML) and all of white matter (WM). Results from 10-fold nested cross validation are reported as mean accuracy, precision, and recall with standard deviation in brackets. The best result we achieved was in the two-class problem NC versus AD + LBD with total accuracy of 0.98 (0.04). In the three-class problem AD versus LBD versus NC and the two-class problem AD versus LBD, we achieved 0.87 (0.08) and 0.74 (0.16), respectively. The performance using 3DT1 images was notably better than when using FLAIR images. The results from the WM region gave similar results as in the WML region. Our study demonstrates that LBP texture analysis in brain MR images can be successfully used for computer based dementia diagnosis.
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9. |
- Zhong, J, et al.
(author)
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Cerenkov luminescence tomography for in vivo radiopharmaceutical imaging
- 2011
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In: International journal of biomedical imaging. - : Hindawi Limited. - 1687-4196 .- 1687-4188. ; 2011, s. 641618-
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Journal article (peer-reviewed)abstract
- Cerenkov luminescence imaging (CLI) is a cost-effective molecular imaging tool for biomedical applications of radiotracers. The introduction of Cerenkov luminescence tomography (CLT) relative to planar CLI can be compared to the development of X-ray CT based on radiography. With CLT, quantitative and localized analysis of a radiopharmaceutical distribution becomes feasible. In this contribution, a feasibility study ofin vivoradiopharmaceutical imaging in heterogeneous medium is presented. Coupled with a multimodalin vivoimaging system, this CLT reconstruction method allows precise anatomical registration of the positron probe in heterogeneous tissues and facilitates the more widespread application of radiotracers. Source distribution inside the small animal is obtained from CLT reconstruction. The experimental results demonstrated that CLT can be employed as an availablein vivotomographic imaging of charged particle emitters in a heterogeneous medium.
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