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Geometric Loss for Deep Multiple Sclerosis lesion Segmentation [article]

Hang Zhang, Jinwei Zhang, Rongguang Wang, Qihao Zhang, Susan A. Gauthier, Pascal Spincemaille, Thanh D. Nguyen, Yi Wang
2020 arXiv   pre-print
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

Maria A. Rocca, Marco Battaglini, Ralph H.B. Benedict, Nicola De Stefano, Jeroen J.G. Geurts, Roland G. Henry, Mark A. Horsfield, Mark Jenkinson, Elisabetta Pagani, Massimo Filippi
2016 Neurology  
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]

Simon K. Warfield, Carl-Fredrik Westin, Charles R. G. Guttmann, Marilyn Albert, Ferenc A. Jolesz, Ron Kikinis
1999 Lecture Notes in Computer Science  
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]

Martin Kolarik, Radim Burget, Carlos M. Travieso-Gonzalez, Jan Kocica
2020 arXiv   pre-print
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]

Christoph Baur, Shadi Albarqouni, Nassir Navab
2017 arXiv   pre-print
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]

Christoph Baur, Shadi Albarqouni, Nassir Navab
2017 Lecture Notes in Computer Science  
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

Guozhi Tao, Sushmita Datta, Renjie He, Flavia Nelson, Jerry S. Wolinsky, Ponnada A. Narayana
2009 Journal of the Neurological Sciences  
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

V. Preethi, Harshvarddhan Singh, Atmaja Raman, Abhishek Jaiswal
2020 International Journal of Engineering Applied Sciences and Technology  
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

Elisabeth Solana, Eloy Martinez-Heras, Victor Montal, Eduard Vilaplana, Elisabet Lopez-Soley, Joaquim Radua, Nuria Sola-Valls, Carmen Montejo, Yolanda Blanco, Irene Pulido-Valdeolivas, Maria Sepúlveda, Magi Andorra (+7 others)
2021 Scientific Reports  
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

H. Vrenken, M. Jenkinson, M. A. Horsfield, M. Battaglini, R. A. van Schijndel, E. Rostrup, J. J. G. Geurts, E. Fisher, A. Zijdenbos, J. Ashburner, D. H. Miller, M. Filippi (+5 others)
2012 Journal of Neurology  
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

Christian Barillot, Gilles Edan, Olivier Commowick
2016 Medical Image Analysis  
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]

Veronica Ravano, Michaela Andelova, Mario Joao Fartaria, Mazen Fouad A-Wali Mahdi, Benedicte Marechal, Reto Meuli, Tomas Uher, Jan Krasensky, Manuela Vaneckova, Dana Horakova, Tobias Kober, Jonas Richiardi
2021 medRxiv   pre-print
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

João Manuel R. S. Tavares
2020 Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization  
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

Fang F. Yu, Florence L. Chiang, Nicholas Stephens, Susie Y. Huang, Berkin Bilgic, Bundhit Tantiwongkosi, Rebecca Romero
2018 Neuroradiology  
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

Mostafa Salem, Sergi Valverde, Mariano Cabezas, Deborah Pareto, Arnau Oliver, Joaquim Salvi, Àlex Rovira, Xavier Lladó
2019 NeuroImage: Clinical  
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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