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https://www.readbyqxmd.com/read/28227985/a-multi-criteria-evaluation-platform-for-segmentation-algorithms
#1
Pierre Laurent, Thierry Cresson, Carlos Vazquez, Nicola Hagemeister, Jacques A de Guise, Pierre Laurent, Thierry Cresson, Carlos Vazquez, Nicola Hagemeister, Jacques A de Guise, Thierry Cresson, Carlos Vazquez, Nicola Hagemeister, Jacques A de Guise, Pierre Laurent
The purpose of this paper is to present a platform for evaluating segmentation algorithms that detect anatomical structures in medical images. Structure detection being subject to human interpretation, we first describe a method to define a ground truth model, i.e. a generated bronze standard, that will be the reference for subsequent analysis. This bronze standard will be characterized in order to retrieve its confidence level that will later be used to normalize the algorithm evaluation. We then describe how the developed platform helps in evaluating algorithm performances described using five evaluation criteria: accuracy, reliability, robustness, under/over segmentation sensitivity and outlier sensitivity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227984/preliminary-study-on-the-automated-skull-fracture-detection-in-ct-images-using-black-hat-transform
#2
Ayumi Yamada, Atsushi Teramoto, Tomoko Otsuka, Kohei Kudo, Hirofumi Anno, Hiroshi Fujita, Ayumi Yamada, Atsushi Teramoto, Tomoko Otsuka, Kohei Kudo, Hirofumi Anno, Hiroshi Fujita, Tomoko Otsuka, Hiroshi Fujita, Ayumi Yamada, Kohei Kudo, Hirofumi Anno, Atsushi Teramoto
Linear skull fracture, following head trauma, may reach major blood vessels, such as the middle meningeal artery or sinus venosus, and may cause epidural hematoma. However, hematoma is likely to be missed in the initial interpretation because it spreads only gradually. In addition, the fracture lines that run along the scan slice plane are often missed during initial interpretation. In this study, we develop a novel method for automated detection of the linear skull fracture using head computed tomography (CT) images and conduct a basic evaluation using digital phantom and head phantom that enclose genuine human bones...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227865/a-dce-mri-imaging-based-model-for-simulation-of-vascular-tumour-growth
#3
Thais Roque, Veerle Kersemans, Sean Smart, Danny Allen, Julia A Schnabel, Michael Chappell, Thais Roque, Veerle Kersemans, Sean Smart, Danny Allen, Julia A Schnabel, Michael Chappell, Sean Smart, Michael Chappell, Veerle Kersemans, Danny Allen, Julia A Schnabel, Thais Roque
Imaging-based modelling of tumour growth can serve as a powerful tool to understand and predict tumour evolution and its response to therapy. The purpose of this study was to introduce, calibrate and evaluate a multi-scale model of vascular tumour growth. The model allows for proliferation, death and spatial spread of tumour cells as well as for new vessel creation. Both the calibration and the evaluation of the tumour growth model were performed using pre-clinical longitudinal time series of dynamic contrast-enhanced magnetic resonance imaging of colon carcinoma...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227864/automatic-segmentation-of-multimodal-brain-tumor-images-based-on-classification-of-super-voxels
#4
M Kadkhodaei, S Samavi, N Karimi, H Mohaghegh, S M R Soroushmehr, K Ward, A All, K Najarian, M Kadkhodaei, S Samavi, N Karimi, H Mohaghegh, S M R Soroushmehr, K Ward, A All, K Najarian, K Ward, S M R Soroushmehr, A All, S Samavi, M Kadkhodaei, H Mohaghegh, K Najarian, N Karimi
Despite the rapid growth in brain tumor segmentation approaches, there are still many challenges in this field. Automatic segmentation of brain images has a critical role in decreasing the burden of manual labeling and increasing robustness of brain tumor diagnosis. We consider segmentation of glioma tumors, which have a wide variation in size, shape and appearance properties. In this paper images are enhanced and normalized to same scale in a preprocessing step. The enhanced images are then segmented based on their intensities using 3D super-voxels...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227861/classification-of-brain-disease-from-magnetic-resonance-images-based-on-multi-level-brain-partitions
#5
Tao Li, Wensheng Zhang, Tao Li, Wensheng Zhang, Wensheng Zhang, Tao Li
In this paper, we present a classification method based on the multi-level brain partitions. Bag-of-visual-words model is used. Firstly, the representative SIFT features are extracted from brain template as the basic visual words. Secondly, individual MR images are described using the basic visual words and support vector machine classifiers are trained for different brain partitions respectively. Thirdly, the final classification is derived from the combination of multiple classifiers. We apply this method to MR images of Alzheimer's disease and Parkinson's disease...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227768/measures-of-the-brain-functional-network-that-correlate-with-alzheimer-s-neuropsychological-test-scores-an-fmri-and-graph-analysis-study
#6
Soroosh Golbabaei, Amin Dadashi, Hamid Soltanian-Zadeh, Soroosh Golbabaei, Amin Dadashi, Hamid Soltanian-Zadeh, Soroosh Golbabaei, Amin Dadashi, Hamid Soltanian-Zadeh
Neural degeneration in Alzheimer's disease (AD) leads to structural topology deformation that in turn changes brain functionality. The main aim of the present study is to find the brain's functional connectivity network (FCN) correlates of Alzheimer's psychological test scores. To this end, the brain's FCN is extracted from the resting state functional magnetic resonance images (rs-fMRI) of healthy controls and patients with AD and represented as a graph. Then, network measures are calculated from the graphs...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227657/an-algorithm-for-accurate-needle-orientation
#7
Yifan Yang, Amr Ahmed, Shigang Yue, Xiang Xie, Hong Chen, Zhihua Wang, Yifan Yang, Amr Ahmed, Shigang Yue, Xiang Xie, Hong Chen, Zhihua Wang, Zhihua Wang, Yifan Yang, Shigang Yue, Hong Chen, Xiang Xie, Amr Ahmed
For the early diagnosis and treatment, a needle insertion for biopsy and treatment is a common and important means. To solve the low accuracy and high probability of repeat surgery in traditional surgical procedures, a computer-assisted system is an effective solution. In such a system, how to acquire the accurate orientation of the surgical needle is one of the most important factors. This paper proposes a "Center Point Method" for needle axis extraction with high accuracy. The method makes full use of edge points from two sides of the needle in image and creates center points through which an accurate axis is extracted...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227647/a-feasibility-study-of-depth-image-based-intent-recognition-for-lower-limb-prostheses
#8
Huseyin Atakan Varol, Yerzhan Massalin, Huseyin Atakan Varol, Yerzhan Massalin, Huseyin Atakan Varol, Yerzhan Massalin
This paper presents our preliminary work on a depth camera based intent recognition system intended for future use in robotic prosthetic legs. The approach infers the activity mode of the subject for standing, walking, running, stair ascent and stair descent modes only using data from the depth camera. Depth difference images are also used to increase the performance of the approach by discriminating between static and dynamic instances. After confidence map based filtering, simple features such as mean, maximum, minimum and standard deviation are extracted from rectangular regions of the frames...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227576/a-fundamental-study-on-visual-impairment-evaluation-using-n170
#9
Takayuki Ishii, Masaki Kyoso, Takayuki Ishii, Masaki Kyoso, Takayuki Ishii, Masaki Kyoso
Progressive population aging has created many problems. Many aged people suffers from cataract because prevalence of cataract in advanced age is far higher than younger people. In this study, we have focused on N170 as a visibility-related signal for quantitative evaluation of cataract. In this report, basic evaluation of N170 in presenting numerical images which had different contrasts was performed. Amplitude and latency were extracted from N170, and then relations to the contrasts of the images were checked...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227423/dynamic-mapping-of-ventricular-function-from-cardiovascular-magnetic-resonance-imaging
#10
Maria Panayiotou, Peter Mountney, Alexander Brost, Daniel Toth, Tom Jackson, Jonathan M Behar, Christopher A Rinaldi, R James Housden, Kawal S Rhode, Maria Panayiotou, Peter Mountney, Alexander Brost, Daniel Toth, Tom Jackson, Jonathan M Behar, Christopher A Rinaldi, R James Housden, Kawal S Rhode, Alexander Brost, Tom Jackson, Maria Panayiotou, Christopher A Rinaldi, Jonathan M Behar, R James Housden, Kawal S Rhode, Daniel Toth, Peter Mountney
Heart failure is associated with substantial mortality and morbidity and remains the most common diagnosis in older patients. Based on experimental electrophysiologic studies, cardiac resynchronization therapy (CRT) for heart failure results in a maximum resynchronization effect when applied to the most delayed left ventricular (LV) site. Current clinical practice is to identify the optimal site using separate visualisation of scar and activation information. These must be mentally mapped into 3D, which is challenging and time-consuming for the electrophysiologist...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227422/a-probabilistic-framework-based-on-slic-superpixel-and-gaussian-processes-for-segmenting-nerves-in-ultrasound-images
#11
Julian Gil Gonzalez, Mauricio A Alvarez, Alvaro A Orozco, Julian Gil Gonzalez, Mauricio A Alvarez, Alvaro A Orozco, Mauricio A Alvarez, Julian Gil Gonzalez, Alvaro A Orozco
We deal with an important problem in the field of anesthesiology known as automatic segmentation of nerve structures depicted in ultrasound images. This is important to aid the experts in anesthesiology, in order to carry out Peripheral Nerve Blocking (PNB). Ultrasound imaging has gained recent interest for performing PNB procedures since it offers a non-invasive visualization of the nerve and the anatomical structures around it. However, the location of these nerves in ultrasound images is a difficult task for the specialist due to the artifacts (i...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227420/automated-in-vivo-delineation-of-lumen-wall-using-intravascular-ultrasound-imaging
#12
Debarghya China, Manas K Nag, K M Mandana, Anup K Sadhu, Pabitra Mitra, Chandan Chakraborty, Debarghya China, Manas K Nag, K M Mandana, Anup K Sadhu, Pabitra Mitra, Chandan Chakraborty, Chandan Chakraborty, Manas K Nag, Debarghya China, Pabitra Mitra, Anup K Sadhu, K M Mandana
This paper presents a novel methodology for automated detection and extraction of the lumen wall from Intravascular Ultrasound (IVUS) frames. IVUS is an in-vivo pull back imaging technique and provides a sequential frame of images for diagnosis of atherosclerotic heart disease. The detection and segmentation of lumen wall is necessary for predicting the arterial wall blockage. Lumen wall is recognized and segmented with the help of seed refinement and random walks algorithms, in tunica and lumen area. The proposed methodology was tested on 147 frames of 13 patients...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227416/3d-2d-ultrasound-feature-based-registration-for-navigated-prostate-biopsy-a-feasibility-study
#13
Sonia Y Selmi, Emmanuel Promayon, Jocelyne Troccaz, Sonia Y Selmi, Emmanuel Promayon, Jocelyne Troccaz, Emmanuel Promayon, Sonia Y Selmi, Jocelyne Troccaz
The aim of this paper is to describe a 3D-2D ultrasound feature-based registration method for navigated prostate biopsy and its first results obtained on patient data. A system combining a low-cost tracking system and a 3D-2D registration algorithm was designed. The proposed 3D-2D registration method combines geometric and image-based distances. After extracting features from ultrasound images, 3D and 2D features within a defined distance are matched using an intensity-based function. The results are encouraging and show acceptable errors with simulated transforms applied on ultrasound volumes from real patients...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227412/development-of-a-real-time-lumbar-ultrasound-image-processing-system-for-epidural-needle-entry-site-localization
#14
Yusong Leng, Shuang Yu, Kok Kiong Tan, Philip Tildsley, Alex Tiong Heng Sia, Ban Leong Sng, Yusong Leng, Shuang Yu, Kok Kiong Tan, Philip Tildsley, Alex Tiong Heng Sia, Ban Leong Sng, Yusong Leng, Shuang Yu, Philip Tildsley, Ban Leong Sng, Kok Kiong Tan
A fully-automatic ultrasound image processing system that can determine the needle entry site for epidural anesthesia (EA) in real time is presented in this paper. Neither the knowledge of anesthetists nor additional hardware is required to operate the system, which firstly directs the anesthetists to reach the desired insertion region in the longitudinal view, i.e., lumbar level L3-L4, and then locates the ideal puncture site by instructing the anesthetists to rotate and slightly adjust the position of ultrasound probe...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227405/template-based-rodent-brain-extraction-and-atlas-mapping
#15
Weimin Huang, Jiaqi Zhang, Zhiping Lin, Su Huang, Yuping Duan, Zhongkang Lu, Weimin Huang, Jiaqi Zhang, Zhiping Lin, Su Huang, Yuping Duan, Zhongkang Lu, Jiaqi Zhang, Weimin Huang, Yuping Duan, Zhongkang Lu, Zhiping Lin, Su Huang
Accurate rodent brain extraction is the basic step for many translational studies using MR imaging. This paper presents a template based approach with multi-expert refinement to automatic rodent brain extraction. We first build the brain appearance model based on the learning exemplars. Together with the template matching, we encode the rodent brain position into the search space to reliably locate the rodent brain and estimate the rough segmentation. With the initial mask, a level-set segmentation and a mask-based template learning are implemented further to the brain region...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227400/sulcal-curve-extraction-using-laplace-beltrami-eigenfunction-level-sets
#16
Rosita Shishegar, Mary Tolcos, David W Walker, Leigh A Johnston, Rosita Shishegar, Mary Tolcos, David W Walker, Leigh A Johnston, David W Walker, Mary Tolcos, Leigh A Johnston, Rosita Shishegar
The complexity of the human cortex is demonstrated in the intricate pattern of gyri and sulci that arise from the cortical folding process during development. Quantitative assessment of cortical folding is important in the definition of normal brain development and provides insight into neurodevelopmental disorders. In this work, a method for sulcal curve extraction is proposed that combines the advantages of previously proposed depth based and curvature based methods. The technique, derived from Laplace Beltrami eigenfunction level sets, maps mean curvature on the level sets, and incorporates depth information using extracted sulci and gyri, a characteristic previously attributed only to depth based methods...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227398/radiomic-analysis-of-multi-contrast-brain-mri-for-the-prediction-of-survival-in-patients-with-glioblastoma-multiforme
#17
Ahmad Chaddad, Christian Desrosiers, Matthew Toews, Ahmad Chaddad, Christian Desrosiers, Matthew Toews, Christian Desrosiers, Ahmad Chaddad, Matthew Toews
Image texture features are effective at characterizing the microstructure of cancerous tissues. This paper proposes predicting the survival times of glioblastoma multiforme (GBM) patients using texture features extracted in multi-contrast brain MRI images. Texture features are derived locally from contrast enhancement, necrosis and edema regions in T1-weighted post-contrast and fluid-attenuated inversion-recovery (FLAIR) MRIs, based on the gray-level co-occurrence matrix representation. A statistical analysis based on the Kaplan-Meier method and log-rank test is used to identify the texture features related with the overall survival of GBM patients...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227388/learning-to-distinguish-cerebral-vasculature-data-from-mechanical-chatter-in-india-ink-images-acquired-using-knife-edge-scanning-microscopy
#18
Michael R Nowak, Yoonsuck Choe, Michael R Nowak, Yoonsuck Choe, Michael R Nowak, Yoonsuck Choe
We introduce a simple, yet effective, procedure for accurate classification of connected components embedded in biological images. In our method, a training set is generated from user-delineated features of manually-labeled examples; we subsequently train a classifier using the resultant training set. The overall process is described using imaging data acquired from an India-ink perfused C57BL/6J mouse brain using Knife Edge Scanning Microscopy. We illustrate the procedure through segmentation of cerebral vasculature structures from mechanical noise using trained classifiers...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227386/image-classification-of-unlabeled-malaria-parasites-in-red-blood-cells
#19
Zheng Zhang, L L Sharon Ong, Kong Fang, Athul Matthew, Justin Dauwels, Ming Dao, Harry Asada, Zheng Zhang, L L Sharon Ong, Kong Fang, Athul Matthew, Justin Dauwels, Ming Dao, Harry Asada, Justin Dauwels, Zheng Zhang, Kong Fang, Ming Dao, Harry Asada
This paper presents a method to detect unlabeled malaria parasites in red blood cells. The current "gold standard" for malaria diagnosis is microscopic examination of thick blood smear, a time consuming process requiring extensive training. Our goal is to develop an automate process to identify malaria infected red blood cells. Major issues in automated analysis of microscopy images of unstained blood smears include overlapping cells and oddly shaped cells. Our approach creates robust templates to detect infected and uninfected red cells...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227384/automatic-classification-of-cancer-cells-in-multispectral-microscopic-images-of-lymph-node-samples
#20
Gali Zimmerman-Moreno, Irina Marin, Moshe Lindner, Iris Barshack, Yuval Garini, Eli Konen, Arnaldo Mayer, Gali Zimmerman-Moreno, Irina Marin, Moshe Lindner, Iris Barshack, Yuval Garini, Eli Konen, Arnaldo Mayer, Moshe Lindner, Yuval Garini, Gali Zimmerman-Moreno, Arnaldo Mayer, Eli Konen, Iris Barshack, Irina Marin
Histopathological analysis is crucial for the diagnosis of a large number of cancer types. A lot of progress has been made in the development of molecular based assays, but many of the cases still require the careful analysis of the stained tissue under a bright-field microscope and its analysis. This procedure is costly and time-consuming. We present a novel method for classification of cancer cells in lymph node images. It is based on the measurement of the spectral image of hematoxylin and eosin stained sample under the microscope and the analysis of the acquired data using state of the art machine learning techniques...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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