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Geometric Loss for Deep Multiple Sclerosis lesion Segmentation
[article]
2020
arXiv
pre-print
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Multiple sclerosis (MS) lesions occupy a small fraction of the brain volume, and are heterogeneous with regards to shape, size and locations, which poses a great challenge for training deep learning based ...
We further develop and instantiate two loss functions containing first- and second-order geometric information of lesion regions to enforce regularization on optimizing deep segmentation models. ...
In this paper, we propose a generalized geometric Loss (GEO loss) formula for MS lesion segmentation. ...
arXiv:2009.13755v1
fatcat:tjmncz2qsnfxbhe5dkb6ryucxm
Brain MRI atrophy quantification in MS
2016
Neurology
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Neurology ® 2017;88:403-413 GLOSSARY BPF 5 brain parenchymal fraction; CIS 5 clinically isolated syndrome; DGM 5 deep gray matter; GM 5 gray matter; ICV 5 intracranial volume; MS 5 multiple sclerosis; ...
Patients with the main clinical phenotypes of multiple sclerosis (MS) manifest varying degrees of brain atrophy beyond that of normal aging. ...
Neuronal and axonal loss in normal-appearing gray matter and subpial lesions in multiple sclerosis. ...
doi:10.1212/wnl.0000000000003542
pmid:27986875
pmcid:PMC5272969
fatcat:mujeaqh6kbfi7fc6czfrufd5tq
Fractional Segmentation of White Matter
[chapter]
1999
Lecture Notes in Computer Science
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Abnormalities in the white matter of the brain are common to subjects with multiple sclerosis and Alzheimer's disease. ...
We applied this automated image segmentation method to over 996 MRI scans of subjects affected by multiple sclerosis, 72 normal aging subjects and 29 scans of subjects with Alzheimer's disease. ...
Acknowledgements This investigation was supported (in part) by a grant from the National Multiple Sclerosis Society (SW) and by NIH grants P41 RR13218-01, R01 RR11747-01A, P01 CA67165-03 and P01 AG04953 ...
doi:10.1007/10704282_7
fatcat:xqvv2wnoinhkjgfoilylrtkknm
Planar 3D Transfer Learning for End to End Unimodal MRI Unbalanced Data Segmentation
[article]
2020
arXiv
pre-print
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In particular, we evaluate the method on the MICCAI 2016 MS lesion segmentation challenge dataset utilizing solely fluid-attenuated inversion recovery (FLAIR) sequence without brain extraction for training ...
The method is validated by the proposed planar 3D res-u-net network with encoder transferred from the 2D VGG-16, which is applied for a single-stage unbalanced 3D image data segmentation. ...
We plan to focus on further improvement of the unimodal raw MRI image processing method for multiple sclerosis lesion segmentation in the future. ...
arXiv:2011.11557v1
fatcat:7kdzwzpwgfcvrccwx3jgl2yx6q
Semi-Supervised Deep Learning for Fully Convolutional Networks
[article]
2017
arXiv
pre-print
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2017 pre-print arXiv:1703.06000v1 fatcat:7stftsaxabdbpm3isphqp7l2fa
In our experiments on the challenging task of MS Lesion Segmentation, we leverage the proposed framework for the purpose of domain adaptation and report substantial improvements over the baseline model ...
Recently, semi-supervised deep learning has been intensively studied for standard CNN architectures. ...
Benedikt Wiestler, from the Neuroradiology department of Klinikum Rechts der Isar for providing us with their MRI MS Lesion dataset. ...
arXiv:1703.06000v2
fatcat:ht542v2g6jbazcm7fbiey5o6ay
Semi-supervised Deep Learning for Fully Convolutional Networks
[chapter]
2017
Lecture Notes in Computer Science
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In our experiments on the challenging task of MS Lesion Segmentation, we leverage the proposed framework for the purpose of domain adaptation and report substantial improvements over the baseline model ...
Recently, semisupervised deep learning has been intensively studied for standard CNN architectures. ...
Benedikt Wiestler, from the Neuroradiology department of Klinikum Rechts der Isar for providing us with their MRI MS Lesion dataset. ...
doi:10.1007/978-3-319-66179-7_36
fatcat:tgqldjfnhzhn5akjlmoxbgegim
Deep gray matter atrophy in multiple sclerosis: A tensor based morphometry
2009
Journal of the Neurological Sciences
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Tensor based morphometry (TBM) was applied to determine the atrophy of deep gray matter (DGM) structures in 88 relapsing multiple sclerosis (MS) patients. ...
For group analysis of atrophy, an unbiased atlas was constructed from 20 normal brains. ...
Introduction Multiple sclerosis (MS) is the most common central nervous system demyelinating disease in humans. ...
doi:10.1016/j.jns.2008.12.035
pmid:19168189
pmcid:PMC2744867
fatcat:mz456mevb5bfhlhynkdno6h3n4
AN END-TO-END AUTOMATIC PANCREAS SEGMENTATION USING GENERATIVE ADVERSARIAL NETWORKS
2020
International Journal of Engineering Applied Sciences and Technology
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Automated pancreas segmentation based on computed tomography (CT) is an effective method of computer-aided detection for the diagnosis of pancreatic cancer. ...
In this paper, we present a method to accurately segment the pancreas from abdominal CT using Deep Convolutional Generative Adversarial Networks (DCGAN). ...
An automated procedure for segmentation of White Matter lesion of Multiple Sclerosis patient images is performed using a cascade of two 3D patch-wise convolutional neural networks (CNN). ...
doi:10.33564/ijeast.2020.v05i01.111
fatcat:da3zzvlytrhmzmh6boza6rzham
Regional grey matter microstructural changes and volume loss according to disease duration in multiple sclerosis patients
2021
Scientific Reports
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AbstractThe spatio-temporal characteristics of grey matter (GM) impairment in multiple sclerosis (MS) are poorly understood. ...
MD and GM changes were associated with white matter lesion load and with physical and cognitive disability. ...
Acknowledgements The authors are grateful to Dr Núria Bargalló, Cesar Garrido and the IDIBAPS Magnetic resonance imaging facilities for their support during the realization of the study (project IBPS15 ...
doi:10.1038/s41598-021-96132-x
pmid:34413373
pmcid:PMC8376987
fatcat:6qi6jmom7jb4diu6owkm4nexoi
Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis
2012
Journal of Neurology
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Focal lesions and brain atrophy are the most extensively studied aspects of multiple sclerosis (MS), but the image acquisition and analysis techniques used can be further improved, especially those for ...
Image artifacts need special attention given their effects on image analysis results. (2) Automated image segmentation methods integrating the assessment of lesion load and atrophy are desirable. (3) A ...
Introduction Longitudinal magnetic resonance imaging (MRI) studies of focal brain lesions and brain atrophy play an important role in the study of multiple sclerosis (MS) in that they help to improve understanding ...
doi:10.1007/s00415-012-6762-5
pmid:23263472
pmcid:PMC3824277
fatcat:s727aflyjrcrpip7d3nuissbhq
Imaging biomarkers in multiple Sclerosis: From image analysis to population imaging
2016
Medical Image Analysis
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This paper illustrates this issue in one acute neuro-inflammatory pathology: Multiple Sclerosis (MS). ...
MRI has often a low specificity for differentiating between possible pathological changes which could help in discriminating between the different pathological stages or grades. ...
Figure 1 : Epidemiologic study of natural evolution of Multiple Sclerosis disease as a 2-stage course. ...
doi:10.1016/j.media.2016.06.017
pmid:27374128
fatcat:uri6wo5zifbohn2nwquzbkehky
Validating atlas-based lesion disconnectomics in multiple sclerosis: a retrospective multi-centric study
[article]
2021
medRxiv
pre-print
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such as multiple sclerosis. ...
Small-worldness was found to decrease for larger total lesion volumes thereby suggesting a loss of efficiency in brain connectivity of MS patients. ...
We also thank Dimitri Van De Ville for gracefully hosting this project and providing useful feedback and discussion. ...
doi:10.1101/2021.05.03.21256161
fatcat:uqbphsjxfvglxcoz5fy6iz67pe
Editorial Message from the Editor-in-Chief
2020
Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization
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latent multiple sclerosis lesion patterns that are associated to definite multiple sclerosis using lesion masks segmented from baseline MR images; 3) Akbar et al. developed a method for preventing overfitting ...
of hand bones and tendons in highresolution magnetic resonance (MR) images; 8) Ramudu and Babua proposed a new formulation for selective segmentation with a level set model for biomedical MR and computed ...
doi:10.1080/21681163.2019.1708015
fatcat:2xwwe5tvorax3jpoqf4lltjqqe
Characterization of normal-appearing white matter in multiple sclerosis using quantitative susceptibility mapping in conjunction with diffusion tensor imaging
2018
Neuroradiology
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The purpose of our study was to investigate alterations in normal-appearing white matter (NAWM) in multiple sclerosis (MS) using QSM in conjunction with DTI. ...
MS lesions demonstrated significant differences in QS, FA, RD, and R2* compared to HCWM (p < 0.03). These metrics did not show a significant difference between whole-brain NAWM and HCWM. ...
Wei Li for his invaluable help with the MRI protocol and data processing. The authors would also like to acknowledge Mr. Gilbert Gortez for his help with data collection. ...
doi:10.1007/s00234-018-2137-7
pmid:30539215
pmcid:PMC6415662
fatcat:4dv27qfwcjclhbxgtl4q7zztvy
A fully convolutional neural network for new T2-w lesion detection in multiple sclerosis
2019
NeuroImage: Clinical
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Longitudinal magnetic resonance imaging (MRI) has an important role in multiple sclerosis (MS) diagnosis and follow-up. ...
The model was trained end-to-end, simultaneously learning both the DFs and the new T2-w lesions, using a combined loss function. ...
Mostafa Salem holds a grant for obtaining the Ph.D. degree from the Egyptian Ministry of Higher Education. ...
doi:10.1016/j.nicl.2019.102149
pmid:31918065
pmcid:PMC7036701
fatcat:a5mzu6zufjerzecyy4embav3i4
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