| 51. |
- Janzen, David L. I., et al.
(författare)
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Three novel approaches to structural identifiability analysis in mixed-effects models
- 2019
-
Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 1872-7565 .- 0169-2607. ; 171, s. 141-152
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Tidskriftsartikel (refereegranskat)abstract
- Background and objective: Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. Methods: In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. Results: To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Conclusions: Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not possible. (C) 2016 Elsevier Ireland Ltd. All rights reserved.
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| 52. |
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| 53. |
- Juhola, M, et al.
(författare)
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Detection of saccadic eye movements using a non-recursive adaptive digital filter
- 1985
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Ingår i: Computer Methods and Programs in Biomedicine. - 0169-2607. ; 21:2, s. 8-81
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Tidskriftsartikel (refereegranskat)abstract
- Saccadic eye movements provide important information about the neuron system at several levels. In recent years computer analysis of saccades has been adapted for use in clinical work. The most common detection methods do not always function without the user's control and aid. In the present paper a digital filter is described for the detection of saccades. This non-recursive filter unscrambles saccade data which has been collected during the execution of an algorithm. The method is suitable for use with microcomputers. The filter is adaptive. Two concise experiments using the method are described.
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| 54. |
- Karlsson, A, et al.
(författare)
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The ankle strategy for postural control - A comparison between a model-based and a marker-based method
- 1997
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Ingår i: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. - : ELSEVIER SCI IRELAND LTD. - 0169-2607. ; 52:3, s. 165-173
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- When analysing postural control statistical characteristics of the centre of pressure or the ground reaction force are often used. A complement would be to analyse movement strategies as well. The purpose of this Study was to determine to what extent the
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| 55. |
- Kindlund, E, et al.
(författare)
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GRAT--genome-scale rapid alignment tool
- 2007
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Ingår i: Computer methods and programs in biomedicine. - : Elsevier BV. - 0169-2607. ; 86:1, s. 87-92
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Tidskriftsartikel (refereegranskat)
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| 56. |
- Koch, S, et al.
(författare)
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Controlled diagnosis-oriented enhancement of automatically segmented radiographs in dentistry
- 1998
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Ingår i: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. - : ELSEVIER SCI IRELAND LTD. - 0169-2607. ; 57:1-2, s. 125-131
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Tidskriftsartikel (refereegranskat)abstract
- A method for controlled diagnosis-oriented enhancement of selected regions of interest in intraoral radiographs is presented. Image enhancement is accomplished by adaptive non-linear grey scale transformation depending on the result of objective quality m
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| 57. |
- Koch, S, et al.
(författare)
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IT-based evaluation and automatic improvement of the quality of intraoral radiographs
- 1995
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Ingår i: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. - : ELSEVIER SCI PUBL IRELAND LTD. - 0169-2607. ; 46:1, s. 41-50
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Tidskriftsartikel (refereegranskat)abstract
- The quality of intraoral radiographs made in dental practices is too often not adequate for diagnostic purposes. This necessitates standardized measures for the quality of intraoral radiographs and controlled techniques for automatic image improvement. Fo
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| 58. |
- Kundu, M. K., et al.
(författare)
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Interactive radiographic image retrieval system
- 2017
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier. - 0169-2607 .- 1872-7565. ; 139, s. 209-220
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Tidskriftsartikel (refereegranskat)abstract
- Background and Objective Content based medical image retrieval (CBMIR) systems enable fast diagnosis through quantitative assessment of the visual information and is an active research topic over the past few decades. Most of the state-of-the-art CBMIR systems suffer from various problems: computationally expensive due to the usage of high dimensional feature vectors and complex classifier/clustering schemes. Inability to properly handle the “semantic gap” and the high intra-class versus inter-class variability problem of the medical image database (like radiographic image database). This yields an exigent demand for developing highly effective and computationally efficient retrieval system. Methods We propose a novel interactive two-stage CBMIR system for diverse collection of medical radiographic images. Initially, Pulse Coupled Neural Network based shape features are used to find out the most probable (similar) image classes using a novel “similarity positional score” mechanism. This is followed by retrieval using Non-subsampled Contourlet Transform based texture features considering only the images of the pre-identified classes. Maximal information compression index is used for unsupervised feature selection to achieve better results. To reduce the semantic gap problem, the proposed system uses a novel fuzzy index based relevance feedback mechanism by incorporating subjectivity of human perception in an analytic manner. Results Extensive experiments were carried out to evaluate the effectiveness of the proposed CBMIR system on a subset of Image Retrieval in Medical Applications (IRMA)-2009 database consisting of 10,902 labeled radiographic images of 57 different modalities. We obtained overall average precision of around 98% after only 2–3 iterations of relevance feedback mechanism. We assessed the results by comparisons with some of the state-of-the-art CBMIR systems for radiographic images. Conclusions Unlike most of the existing CBMIR systems, in the proposed two-stage hierarchical framework, main importance is given on constructing efficient and compact feature vector representation, search-space reduction and handling the “semantic gap” problem effectively, without compromising the retrieval performance. Experimental results and comparisons show that the proposed system performs efficiently in the radiographic medical image retrieval field.
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| 59. |
- LEMAITRE, D, et al.
(författare)
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ARTEMIS-2 - AN APPLICATION DEVELOPMENT EXPERIMENT WITH THE HELIOS ENVIRONMENT
- 1994
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Ingår i: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. - : ELSEVIER SCI PUBL IRELAND LTD. - 0169-2607. ; 45, s. S127-S138
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- A medical application is a highly complex system that embraces many data types and a very large number of data processing functions and methods. The development of integrated software engineering environments has deeply changed the conception of applicati
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| 60. |
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| 61. |
- Lindbom, Lars, et al.
(författare)
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Perl-speaks-NONMEM (PsN) – a Perl module for NONMEM related programming
- 2004
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 75:2, s. 85-94
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Tidskriftsartikel (refereegranskat)abstract
- The NONMEM program is the most widely used nonlinear regression software in population pharmacokinetic/pharmacodynamic (PK/PD) analyses. In this article we describe a programming library, Perl-speaks-NONMEM (PsN), intended for programmers that aim at using the computational capability of NONMEM in external applications. The library is object oriented and written in the programming language Perl. The classes of the library are built around NONMEM's data, model and output files. The specification of the NONMEM model is easily set or changed through the model and data file classes while the output from a model fit is accessed through the output file class. The classes have methods that help the programmer perform common repetitive tasks, e.g. summarising the output from a NONMEM run, setting the initial estimates of a model based on a previous run or truncating values over a certain threshold in the data file. PsN creates a basis for the development of high-level software using NONMEM as the regression tool.
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| 62. |
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| 63. |
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| 64. |
- Liuhanen, Sasu, et al.
(författare)
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Indirect measurement of the vascular endothelial glycocalyx layer thickness in human submucosal capillaries with a plug-in for ImageJ
- 2013
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 110:1, s. 38-47
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND:The thickness of vascular endothelial glycocalyx layer can be measured indirectly during a spontaneous leukocyte passage from oral submucosal capillaries in humans. The subsequent differences in red blood cell (RBC) column widths, before a spontaneous white blood cell passage (pre-WBC) and after a spontaneous WBC passage (post-WBC) can be used in off-line analysis to measure glycocalyx thickness: [pre-WBC width-post-WBC width]/2. We created and validated a semi-automatic plug-in for ImageJ to measure the endothelial glycocalyx layer thickness.METHODS:Video clips presenting human sublingual microvasculature were created with a side-stream dark field imaging device. Spontaneous leukocyte passages in capillaries were analyzed from video clips with ImageJ. The capillary glycocalyx layer thickness was measured by the indirect approach with two manual and two semi-automatic methods.RESULTS: There were no statistically significant differences between glycocalyx layer thicknesses measured with different methods, even though small inter-method differences in RBC column thicknesses could be detected. Inter-rater differences were systematically smaller with both semi-automatic methods. Intra-rater coefficient of variation [CV] (95% CI) was largest when measurements were made completely manually [9.2% (8.4-10.0)], but improved significantly with automatic image enhancement prior to manual measurement [7.2% (6.4-8.0)]. CV could be improved further when using semi-automatic analysis with an in-frame median filter radius of 1 pixel [5.8% (5.0-6.6)], or a median filter radius of 2 pixels [4.3% (3.5-5.1)].CONCLUSIONS: Semi-automatic analysis of glycocalyx decreased the intra-rater CV and the inter-rater differences compared to the manual method. On average, each of the four methods yielded equal results for the glycocalyx thickness. Being the only feasible bed side method in most clinical scenarios, indirect measurement of glycocalyx thickness with orthogonal polarization spectral imaging or side-stream dark field imaging device and our plug-in can advance the study of glycocalyx layer pathology in man.
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| 65. |
- Lundsberg, Jonathan, et al.
(författare)
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Compressed spike-triggered averaging in iterative decomposition of surface EMG
- 2023
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607. ; 228
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Tidskriftsartikel (refereegranskat)abstract
- Background and Objective: Analysis of motor unit activity is important for assessing and treating diseases or injuries affecting natural movement. State-of-the-art decomposition translates high-density surface electromyography (HDsEMG) into motor unit activity. However, current decomposition methods offer far from complete separation of all motor units. Methods: This paper proposes a peel-offapproach to automatic decomposition of HDsEMG into motor unit action potential (MUAP) trains, based on the Fast Independent Component Analysis algorithm (FastICA). The novel steps include utilizing compression by means of Principal Component Analysis and spike-triggered averaging, to estimate surface MUAP distributions with less noise, which are iteratively subtracted from the HDsEMG dataset. Furthermore, motor unit spike trains are estimated by highdimensional density-based clustering of peaks in the FastICA source output. And finally, a new reliability measure is used to discard poor motor unit estimates by comparing the variance of the FastICA source output before and after the peel-offstep. The method was validated using reconstructed synthetic data at three different signal-to-noise levels and was compared to an established deflationary FastICA approach. Results: Both algorithms had very high recall and precision, over 90%, for spikes from matching motor units, referred to as matched performance. However, the peel-offalgorithm correctly identified more motor units for all noise levels. When accounting for unidentified motor units, total recall was up to 33 percentage points higher; and when accounting for duplicate estimates, total precision was up to 24 percentage points higher, compared to the state-of-the-art reference. In addition, a comparison was done using experimental data where the proposed algorithm had a matched recall of 97% and precision of 85% with respect to the reference algorithm. Conclusion: These results show a substantial performance increase for decomposition of simulated HDsEMG data and serve to validate the proposed approach. This performance increase is an important step towards complete decomposition and extraction of information of motor unit activity. (C) 2022TheAuthor(s). PublishedbyElsevierB.V.
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| 66. |
- Mahbod, A., et al.
(författare)
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Transfer learning using a multi-scale and multi-network ensemble for skin lesion classification
- 2020
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 193, s. 105475-
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Tidskriftsartikel (refereegranskat)abstract
- Background and objective: Skin cancer is among the most common cancer types in the white population and consequently computer aided methods for skin lesion classification based on dermoscopic images are of great interest. A promising approach for this uses transfer learning to adapt pre-trained convolutional neural networks (CNNs) for skin lesion diagnosis. Since pre-training commonly occurs with natural images of a fixed image resolution and these training images are usually significantly smaller than dermoscopic images, downsampling or cropping of skin lesion images is required. This however may result in a loss of useful medical information, while the ideal resizing or cropping factor of dermoscopic images for the fine-tuning process remains unknown. Methods: We investigate the effect of image size for skin lesion classification based on pre-trained CNNs and transfer learning. Dermoscopic images from the International Skin Imaging Collaboration (ISIC) skin lesion classification challenge datasets are either resized to or cropped at six different sizes ranging from 224 × 224 to 450 × 450. The resulting classification performance of three well established CNNs, namely EfficientNetB0, EfficientNetB1 and SeReNeXt-50 is explored. We also propose and evaluate a multi-scale multi-CNN (MSM-CNN) fusion approach based on a three-level ensemble strategy that utilises the three network architectures trained on cropped dermoscopic images of various scales. Results: Our results show that image cropping is a better strategy compared to image resizing delivering superior classification performance at all explored image scales. Moreover, fusing the results of all three fine-tuned networks using cropped images at all six scales in the proposed MSM-CNN approach boosts the classification performance compared to a single network or a single image scale. On the ISIC 2018 skin lesion classification challenge test set, our MSM-CNN algorithm yields a balanced multi-class accuracy of 86.2% making it the currently second ranked algorithm on the live leaderboard. Conclusions: We confirm that the image size has an effect on skin lesion classification performance when employing transfer learning of CNNs. We also show that image cropping results in better performance compared to image resizing. Finally, a straightforward ensembling approach that fuses the results from images cropped at six scales and three fine-tuned CNNs is shown to lead to the best classification performance.
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| 67. |
- Malm, Patrik, et al.
(författare)
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Debris removal in Pap-smear images
- 2013
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 111:1, s. 128-138
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Tidskriftsartikel (refereegranskat)abstract
- Since its introduction in the 1940s the Pap-smear test has helped reduce the incidence of cervical cancer dramatically in countries where regular screening is standard. The automation of this procedure is an open problem that has been ongoing for over fifty years without reaching satisfactory results. Existing systems are discouragingly expensive and yet they are only able to make a correct distinction between normal and abnormal samples in a fraction of cases. Therefore, they are limited to acting as support for the cytotechnicians as they perform their manual screening. The main reason for the current limitations is that the automated systems struggle to overcome the complexity of the cell structures. Samples are covered in artefacts such as blood cells, overlapping and folded cells, and bacteria, that hamper the segmentation processes and generate large number of suspicious objects. The classifiers designed to differentiate between normal cells and pre-cancerous cells produce unpredictable results when classifying artefacts. In this paper, we propose a sequential classification scheme focused on removing unwanted objects, debris, from an initial segmentation result, intended to be run before the actual normal/abnormal classifier. The method has been evaluated using three separate datasets obtained from cervical samples prepared using both the standard Pap-smear approach as well as the more recent liquid based cytology sample preparation technique. We show success in removing more than 99% of the debris without loosing more than around one percent of the epithelial cells detected by the segmentation process.
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| 68. |
- Malusek, Alexandr, et al.
(författare)
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CTmod : a toolkit for Monte Carlo simulation of projections including scatter in computed tomography
- 2008
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier. - 0169-2607 .- 1872-7565. ; 90:2, s. 167-178
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Tidskriftsartikel (refereegranskat)abstract
- The CTmod toolkit is a set of C++ class libraries based on the CERN’s application development framework ROOT. It uses the Monte Carlo method to simulate energy imparted to a CT-scanner detector array. Photons with a given angle–energy distribution are emitted from the X-ray tube approximated by a point source, transported through a phantom, and their contribution to the energy imparted per unit surface area of each detector element is scored. Alternatively, the scored quantity may be the fluence, energy fluence, plane fluence, plane energy fluence, or kerma to air in the center of each detector element. Phantoms are constructed from homogenous solids or voxel arrays via overlapping. Implemented photon interactions (photoelectric effect, coherent scattering, and incoherent scattering) are restricted to the energy range from 10 to 200 keV. Variance reduction techniques include the collision density estimator and survival biasing combined with the Russian roulette. The toolkit has been used to estimate the amount of scatter in cone beam computed tomography and planar radiography.
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| 69. |
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| 70. |
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| 71. |
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| 72. |
- Matuszewski, Damian J., et al.
(författare)
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Reducing the U-Net size for practical scenarios : Virus recognition in electron microscopy images
- 2019
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Ingår i: Computer Methods and Programs in Biomedicine. - : ELSEVIER IRELAND LTD. - 0169-2607 .- 1872-7565. ; 178, s. 31-39
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Tidskriftsartikel (refereegranskat)abstract
- Background and objective: Convolutional neural networks (CNNs) offer human experts-like performance and in the same time they are faster and more consistent in their prediction. However, most of the proposed CNNs require an expensive state-of-the-art hardware which substantially limits their use in practical scenarios and commercial systems, especially for clinical, biomedical and other applications that require on-the-fly analysis. In this paper, we investigate the possibility of making CNNs lighter by parametrizing the architecture and decreasing the number of trainable weights of a popular CNN: U-Net. Methods: In order to demonstrate that comparable results can be achieved with substantially less trainable weights than the original U-Net we used a challenging application of a pixel-wise virus classification in Transmission Electron Microscopy images with minimal annotations (i.e. consisting only of the virus particle centers or centerlines). We explored 4 U-Net hyper-parameters: the number of base feature maps, the feature maps multiplier, the number of the encoding-decoding levels and the number of feature maps in the last 2 convolutional layers. Results: Our experiments lead to two main conclusions: 1) the architecture hyper-parameters are pivotal if less trainable weights are to be used, and 2) if there is no restriction on the trainable weights number using a deeper network generally gives better results. However, training larger networks takes longer, typically requires more data and such networks are also more prone to overfitting. Our best model achieved an accuracy of 82.2% which is similar to the original U-Net while using nearly 4 times less trainable weights (7.8 M in comparison to 31.0 M). We also present a network with < 2M trainable weights that achieved an accuracy of 76.4%. Conclusions: The proposed U-Net hyper-parameter exploration can be adapted to other CNNs and other applications. It allows a comprehensive CNN architecture designing with the aim of a more efficient trainable weight use. Making the networks faster and lighter is crucial for their implementation in many practical applications. In addition, a lighter network ought to be less prone to over-fitting and hence generalize better. (C) 2019 Published by Elsevier B.V.
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| 73. |
- Matuszewski, Damian J., et al.
(författare)
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TEM virus images : Benchmark dataset and deep learning classification
- 2021
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier. - 0169-2607 .- 1872-7565. ; 209
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Tidskriftsartikel (refereegranskat)abstract
- Background and Objective: To achieve the full potential of deep learning (DL) models, such as understanding the interplay between model (size), training strategy, and amount of training data, researchers and developers need access to new dedicated image datasets; i.e., annotated collections of images representing real-world problems with all their variations, complexity, limitations, and noise. Here, we present, describe and make freely available an annotated transmission electron microscopy (TEM) image dataset. It constitutes an interesting challenge for many practical applications in virology and epidemiology; e.g., virus detection, segmentation, classification, and novelty detection. We also present benchmarking results for virus detection and recognition using some of the top-performing (large and small) networks as well as a handcrafted very small network. We compare and evaluate transfer learning and training from scratch hypothesizing that with a limited dataset, transfer learning is crucial for good performance of a large network whereas our handcrafted small network performs relatively well when training from scratch. This is one step towards understanding how much training data is needed for a given task.Methods: The benchmark dataset contains 1245 images of 22 virus classes. We propose a representative data split into training, validation, and test sets for this dataset. Moreover, we compare different established DL networks and present a baseline DL solution for classifying a subset of the 14 most-represented virus classes in the dataset.Results: Our best model, DenseNet201 pre-trained on ImageNet and fine-tuned on the training set, achieved a 0.921 F1-score and 93.1% accuracy on the proposed representative test set.Conclusions: Public and real biomedical datasets are an important contribution and a necessity to increase the understanding of shortcomings, requirements, and potential improvements for deep learning solutions on biomedical problems or deploying solutions in clinical settings. We compared transfer learning to learning from scratch on this dataset and hypothesize that for limited-sized datasets transfer learning is crucial for achieving good performance for large models. Last but not least, we demonstrate the importance of application knowledge in creating datasets for training DL models and analyzing their results.
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| 74. |
- Medvedev, Alexander, 1958-, et al.
(författare)
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Oscillations-free PID control of anesthetic drug delivery in neuromuscular blockade
- 2019
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Ingår i: Computer Methods and Programs in Biomedicine. - : ELSEVIER IRELAND LTD. - 0169-2607 .- 1872-7565. ; 171, s. 119-131
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Tidskriftsartikel (refereegranskat)abstract
- Background and Objectives: The PID-control of drug delivery or the neuromuscular blockade (NMB) in closed-loop anesthesia is considered. The NMB system dynamics portrayed by a Wiener model can exhibit sustained nonlinear oscillations under realistic PID gains and for physiologically feasible values of the model parameters. Such oscillations, also repeatedly observed in clinical trials, lead to under- and overdosing of the administered drug and undermine patient safety. This paper proposes a tuning policy for the proportional PID gain that via bifurcation analysis ensures oscillations-free performance of the control loop. Online estimates of the Wiener model parameters are needed for the controller implementation and monitoring of the closed-loop proximity to oscillation.Methods: The nonlinear dynamics of the PID-controlled NMB system are studied by bifurcation analysis. A database of patient models estimated under PID-controlled neuromuscular blockade during general anesthesia is utilized, along with the corresponding clinical measurements. The performance of three recursive algorithms is compared in the application at hand: an extended Kalman filter, a conventional particle filter (PF), and a PF making use of an orthonormal basis to estimate the probability density function from the particle set.Results: It is shown that with a time-varying proportional PID gain, the type of equilibria of the closed-loop system remains the same as in the case of constant controller gains. The recovery time and frequency of oscillations are also evaluated in simulation over the database of patient models. Nonlinear identification techniques based on model linearization yield biased parameter estimates and thus introduce superfluous uncertainty. The bias and variance of the estimated models are related to the computational complexity of the identification algorithms, highlighting the superiority of the PFs in this safety-critical application.Conclusions: The study demonstrates feasibility of the proposed oscillation-free control strategy combining bifurcation theory based design and online parameter estimation by PF.
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| 75. |
- Memedi, Mevludin, 1983-, et al.
(författare)
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A web application for follow-up of results from a mobile device test battery for Parkinson’s disease patients
- 2011
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Ingår i: Computer Methods and Programs in Biomedicine. - Amsterdam : Elsevier BV. - 0169-2607 .- 1872-7565. ; 104:2, s. 219-226
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Tidskriftsartikel (refereegranskat)abstract
- A test battery consisting of self-assessments and motor tests for patients with Parkinson’s disease (PD) was constructed and implemented on a hand computer with touch screen in a telemedicine setting. In this work, a Web-based system was developed to deliver decision support information to treating clinical staff for assessing PD symptoms in their patients. Test results from the hand unit are transferred to a central server and processed into scores for different symptom dimensions and an “overall test score” reflecting the overall condition of the patient during a test period. The IBM Computer System Usability Questionnaire was administered to assess the users’ satisfaction with the system. Results showed that a majority of users who completed the evaluation were quite satisfied with the usability although a sizeable minority were not. Response times were tested by simulating up to 100 users accessing the web application at the same time. The average page completion times were in the range of 0.5 seconds indicating fast response. The system was able to summarize the test-battery data and present them in a useful manner. Its main contribution is a novel way to easily access symptom information from the home environment of patients.
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| 76. |
- Nyberg, Joakim, et al.
(författare)
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PopED : An extended, parallelized, nonlinear mixed effects models optimal design tool
- 2012
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 108:2, s. 789-805
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Tidskriftsartikel (refereegranskat)abstract
- Several developments have facilitated the practical application and increased the general use of optimal design for nonlinear mixed effects models. These developments include new methodology for utilizing advanced pharmacometric models, faster optimization algorithms and user friendly software tools. In this paper we present the extension of theoptimal design software PopED, which incorporates many of these recent advances into aneasily useable enhanced GUI. Furthermore, we present new solutions to problems related to the design of experiments such as: faster and more robust FIM calculations and optimizations, optimizing over cost/utility functions and diagnostic tools and plots to evaluate designperformance. Examples for; (i) Group size optimization and efficiency translation, (ii) Cost/constraint optimization, (iii) Optimizations with different FIM approximations and (iv) optimization with parallel computing demonstrate the new features in PopED and underline the potential use of this tool when designing experiments.
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| 77. |
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| 78. |
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| 79. |
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| 80. |
- Persson, T, et al.
(författare)
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A marker-free method to estimate joint centre of rotation by video image processing
- 1995
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Ingår i: Computer Methods and Programs in Biomedicine. - 0169-2607. ; 46:3, s. 217-224
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Tidskriftsartikel (refereegranskat)abstract
- A marker-free video measurement and image processing method that provides numerical estimation of the 2-D centre of rotation of one rigid segment is tested. The algorithm is based on binary region moment features. A comparison is made between this method
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| 81. |
- Pham, Tuan D
(författare)
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Supervised restoration of degraded medical images using multiple-point geostatistics
- 2012
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier. - 0169-2607 .- 1872-7565. ; 106:3, s. 201-209
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Tidskriftsartikel (refereegranskat)abstract
- Reducing noise in medical images has been an important issue of research and development for medical diagnosis, patient treatment, and validation of biomedical hypotheses. Noise inherently exists in medical and biological images due to the acquisition and transmission in any imaging devices. Being different from image enhancement, the purpose of image restoration is the process of removing noise from a degraded image in order to recover as much as possible its original version. This paper presents a statistically supervised approach for medical image restoration using the concept of multiple-point geostatistics. Experimental results have shown the effectiveness of the proposed technique which has potential as a new methodology for medical and biological image processing.
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| 82. |
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| 83. |
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| 84. |
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| 85. |
- Sarve, Hamid, et al.
(författare)
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Extracting 3D information on bone remodeling in the proximity of titanium implants in SRμCT image volumes.
- 2011
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Ingår i: Computer methods and programs in biomedicine. - : Elsevier BV. - 1872-7565 .- 0169-2607. ; 102:1, s. 25-34
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Tidskriftsartikel (refereegranskat)abstract
- Bone-implant integration is measured in several ways. Traditionally and routinely, 2D histological sections of samples, containing bone and the biomaterial, are stained and analyzed using a light microscope. Such histological section provides detailed cellular information about the bone regeneration in the proximity of the implant. However, this information reflects the integration in only a very small fraction, a 10 μm thick slice, of the sample. In this study, we show that feature values quantified on 2D sections are highly dependent on the orientation and the placement of the section, suggesting that a 3D analysis of the whole sample is of importance for a more complete judgment of the bone structure in the proximity of the implant. We propose features describing the 3D data by extending the features traditionally used for 2D-analysis. We present a method for extracting these features from 3D image data and we measure them on five 3D SRμCT image volumes. We also simulate cuts through the image volume positioned at all possible section positions. These simulations show that the measurement variations due to the orientation of the section around the center line of the implant are about 30%.
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| 86. |
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| 87. |
- Seipel, S, et al.
(författare)
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Oral implant treatment planning in a virtual reality environment
- 1998
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Ingår i: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. - : ELSEVIER SCI IRELAND LTD. - 0169-2607. ; 57:1-2, s. 95-103
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Tidskriftsartikel (refereegranskat)abstract
- A system for three-dimensional oral implant treatment planning is presented. Virtual reality technologies are used in order to improve the human image interpretation and planning performance. The methods described are based on computer tomography (CT) dat
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| 88. |
- Sepehri, Amir A., et al.
(författare)
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A novel method for pediatric heart sound segmentation without using the ECG
- 2010
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 99:1, s. 43-48
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose a novel method for pediatric heart sounds segmentation by paying special attention to the physiological effects of respiration on pediatric heart sounds. The segmentation is accomplished in three steps. First, the envelope of a heart sounds signal is obtained with emphasis on the first heart sound (Si) and the second heart sound (S(2)) by using short time spectral energy and autoregressive (AR) parameters of the signal. Then, the basic heart sounds are extracted taking into account the repetitive and spectral characteristics of Si and S2 sounds by using a Multi-Layer Perceptron (MLP) neural network classifier. In the final step, by considering the diastolic and systolic intervals variations due to the effect of a child's respiration, a complete and precise heart sounds end-pointing and segmentation is achieved.
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| 89. |
- Sepehri, Amir A., et al.
(författare)
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Computerized screening of children congenital heart diseases
- 2008
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Ingår i: Computerized screening of children congenital heart diseases CMPB. - United Kingdom : Elsevier BV. - 0169-2607. ; 92:2, s. 186-192
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose a method for automated screening of congenital heart diseases in children through heart sound analysis techniques. Our method relies on categorizing the pathological murmurs based on the heart sections initiating them. We show that these pathelogical murmur categories can be identified by examining the heart sound energy over specific frequency bands, which we call, Arash-Bands. To specify the Arash-Band for a category, we evaluate the energy of the heart sound over all possible frequency bands. The Arash-Band is the frequency band that provides the lowest error in clustering the instances of that category against the normal ones. The energy content of the Arash-Bands for different categories constitue a feature vector that is suitable for classification using a neural network. In order to train, and to evaluate the performance of the proposed method, we use a training data-bank, as well as a test data-bank, collectively consisting of ninety samples (normal and abnormal). Our results show that in more than 94% of cases, our method correctly identifies children with congenital heart diseases. This percentage improves to 100%, when we use the Jack-Knife validation method over all the 90 samples.
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| 90. |
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| 91. |
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| 92. |
- Sintorn, Ida-Maria, et al.
(författare)
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A refined circular template matching method for classification of human cytomegalovirus capsids in TEM images
- 2004
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607. ; 76, s. 95-102
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Tidskriftsartikel (refereegranskat)abstract
- An automatic image analysis method for describing, segmenting, and classifying Human Cyto\-megalo\-virus capsids in transmission electron micrograph (TEM) images of host cell nuclei has been developed. Three stages of the capsid assembly process in the host cell nucleus have been investigated. Each class is described by a radial density profile, which is the average grey-level at each radial distance from the centre. A template, constructed from the profile, is used to find possible capsid locations by correlation based matching. The matching results are further refined by size and distortion analysis of each possible capsid, resulting in a final segmentation and classification.
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| 93. |
- Sjöberg, Carl, et al.
(författare)
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Multi-atlas based segmentation using probabilistic label fusion with adaptive weighting of image similarity measures
- 2013
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 110:3, s. 308-319
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Tidskriftsartikel (refereegranskat)abstract
- Label fusion multi-atlas approaches for image segmentation can give better segmentation results than single atlas methods. We present a multi-atlas label fusion strategy based on probabilistic weighting of distance maps. Relationships between image similarities and segmentation similarities are estimated in a learning phase and used to derive fusion weights that are proportional to the probability for each atlas to improve the segmentation result. The method was tested using a leave-one-out strategy on a database of 21 pre-segmented prostate patients for different image registrations combined with different image similarity scorings. The probabilistic weighting yields results that are equal or better compared to both fusion with equal weights and results using the STAPLE algorithm. Results from the experiments demonstrate that label fusion by weighted distance maps is feasible, and that probabilistic weighted fusion improves segmentation quality more the stronger the individual atlas segmentation quality depends on the corresponding registered image similarity. The regions used for evaluation of the image similarity measures were found to be more important than the choice of similarity measure.
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| 94. |
- Souza-Pereira, Leonice, et al.
(författare)
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Clinical decision support systems for chronic diseases : A Systematic literature review.
- 2020
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 195, s. 105565-
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Tidskriftsartikel (refereegranskat)abstract
- UNLABELLED: A Clinical Decision Support System (CDSS) aims to assist physicians, nurses and other professionals in decision-making related to the patient's clinical condition. CDSSs deal with pertinent and critical data, and special care should be taken in their design to ensure the development of usable, secure and reliable tools.OBJECTIVE: This paper aims to investigate existing literature dealing with the development process of CDSSs for monitoring chronic diseases, analysing their functionalities and characteristics, and the software engineering representation in their design.METHODS: A systematic literature review (SLR) is conducted to analyse the literature on CDSSs for monitoring chronic diseases and the application of software engineering techniques in their design.RESULTS: Fourteen included studies revealed that the most addressed disease was diabetes (42.8%) and the most commonly proposed approach was diagnostic (85.7%). Regarding data sources, the studies show a predominance on the use of databases (85.7%), with other data sources such as sensors (42.8%) and self-report (28.6%) also being considered. Analysing the representation for engineering techniques, we found Behaviour diagrams (42.8%) to be the most frequent, closely followed by Structural diagrams (35.7%) and others (78.6%) being largely mentioned. Some studies also approached the requirement specification (21.4%). The most common target evaluation was the performance of the system (64.2%) and the most common metric was accuracy (57.1%).CONCLUSION: We conclude that software engineering, in its completeness, has scarce representation in studies focused on the development of CDSSs for chronic diseases.
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| 95. |
- Souza-Pereira, Leonice, et al.
(författare)
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Quality-in-use characteristics for clinical decision support system assessment
- 2021
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 207, s. 106169-106169
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Tidskriftsartikel (refereegranskat)abstract
- Background: Clinical decision support systems (CDSSs) are developed to support healthcare practitioners with decision-making about therapy and diagnosis’ confirmation, among others. Although there are many advantages of using CDSSs, there are still many challenges in their adoption. Therefore, it is essential to ensure the quality of the system, so that it can be used confidently and securely.Objective: This study aims to propose a set of (sub)characteristics which should be considered in evaluating the quality-in-use of CDSSs, based on the ISO/IEC 25010 standard and on existing literature.Methods: We reviewed the existing literature on CDSS assessment and presented a list of quality characteristics evaluated.Results: Ten quality characteristics and 56 sub-characteristics were identified and selected from the literature, in which usability was evaluated the most. An example of a scenario has been presented to illustrate our assessment approach of satisfaction and efficiency as important quality-in-use characteristics to be applied in the evaluation of a CDSS.Conclusion: The proposed approach will contribute in bridging the gap between the quality of CDSSs and their adoption.
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| 96. |
- Stathakis, Sotirios, et al.
(författare)
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gamma(+) index : A new evaluation parameter for quantitative quality assurance
- 2014
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 114:1
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The accuracy dose delivery and the evaluation of differences between calculated and delivered dose distributions, has been studied by several groups. The aim of this investigation is to extend the gamma index by including radiobiological information and to propose a new index that we will here forth refer to as the gamma plus (gamma(+)). Further more, to validate the robustness of this new index in performing a quality control analysis of an IMRT treatment plan using pure radiobiological measures such as the biologically effective uniform dose ((D) over bar) and complication-free tumor control probability (P+). Material and methods: A new quality assurance index, the (gamma(+)), is proposed based on the theoretical concept of gamma index presented by Low et al. (1998). In this study, the dose difference, including the radiobiological dose information (biological effective dose, BED) is used instead of just the physical dose difference when performing the gamma(+) calculation. An in-house software was developed to compare different dose distributions based on the gamma(+) concept. A test pattern for a two-dimensional dose comparison was built using the in-house software platform. The gamma(+) index was tested using planar dose distributions (exported from the treatment planning system) and delivered (film) dose distributions acquired in a solid water phantom using a test pattern and a theoretical clinical case. Furthermore, a lung cancer case for a patient treated with IMRT was also selected for the analysis. The respective planar dose distributions from the treatment plan and the film were compared based on the gamma(+) index and were evaluated using the radiobiological measures of P+ and (D) over bar. Results: The results for the test pattern analysis indicate that the gamma(+) index distributions differ from those of the gamma index since the former considers radiobiological parameters that may affect treatment outcome. For the theoretical clinical case, it is observed that the gamma(+) index varies for different treatment parameters (e.g. dose per fraction). The dose area histogram (DAH) from the plan and film dose distributions are associated with P+ values of 50.8% and 49.0%, for a (D) over bar to the target of 54.0 Gy and 53.3 Gy, respectively. Conclusion: The gamma(+) index shows advantageous properties in the quantitative evaluation of dose delivery and quality control of IMRT treatments because it includes information about the expected responses and radiobiological doses of the individual tissues.
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| 97. |
- Su, Fan-Chi, et al.
(författare)
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A graphic user interface toolkit for specification, report and comparison of dose-response relations and treatment plans using the biologically effective uniform dose
- 2010
-
Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 100:1, s. 69-78
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Tidskriftsartikel (refereegranskat)abstract
- A toolkit (BEUDcal) has been developed for evaluating the effectiveness and for predicting the outcome of treatment plans by calculating the biologically effective uniform dose (BEUD) and complication-free tumor control probability. The input for the BEUDcal is the differential dose-volume histograms of organs exported from the treatment planning system. A clinical database is built for the dose-response parameters of different tumors and normal tissues. Dose-response probabilities of all the examined organs are illustrated together with the corresponding BEUDs and the P+ values. Furthermore, BEUDcal is able to generate a report that simultaneously presents the radiobiological evaluation together with the physical dose indices, showing the complementary relation between the physical and radiobiological treatment plan analysis performed by BEUDcal. Comparisons between treatment plans for helical tomotherapy and multileaf collimator-based intensity modulated radiotherapy of a lung patient were demonstrated to show the versatility of BEUDcal in the assessment and report of dose-response relations.
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| 98. |
- Svahn, Gudmund, et al.
(författare)
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PACS for radiology conferences--improvement of application software
- 1994
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Ingår i: Computer Methods and Programs in Biomedicine. - 0169-2607. ; 43:1-2, s. 81-84
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Tidskriftsartikel (refereegranskat)abstract
- The introduction of PACS in a radiology department means that most functions that are available in the film-based system must be included. One important function is the radiology conference. The handling and application programs of digital workstations are normally not developed for demonstrations of many images in a limited time. This paper describes a workstation with specially designed software for radiology conferences. The application is separated in preparation and presentation of the cases to be demonstrated. Very fast image handling is achieved during the conference because the function is based on the principle of prefetching of the selected images. The images are presented on a large screen with high resolution. The experiences of digital radiology conferences are good. However, reference films from previous examinations create extra work because they have to be shown on the conventional lightbox.
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| 99. |
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| 100. |
- Verikas, Antanas, et al.
(författare)
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Multiple feature sets based categorization of laryngeal images
- 2007
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Ingår i: Computer Methods and Programs in Biomedicine. - Amsterdam : Elsevier. - 0169-2607 .- 1872-7565. ; 85:3, s. 257-266
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Tidskriftsartikel (refereegranskat)abstract
- This paper is concerned with an automated analysis of laryngeal images aiming to categorize the images into three decision classes, namely healthy, nodular, and diffuse. The problem is treated as an image analysis and classification task. Aiming to obtain a comprehensive description of laryngeal images, multiple feature sets exploiting information on image colour, texture, geometry, image intensity gradient direction, and frequency content are extracted. A separate support vector machine (SVM) is used to categorize features of each type into the decision classes. The final image categorization is then obtained based on the decisions provided by a committee of support vector machines. Bearing in mind a high similarity of the decision classes, the correct classification rate of over 94% obtained when testing the system on 785 laryngeal images recorded at the Department of Otolaryngology, Kaunas University of Medicine is rather promising.
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