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pro vyhledávání: '"Collins, D Louis"'
One of the fundamental elements of both traditional and certain deep learning medical image registration algorithms is measuring the similarity/dissimilarity between two images. In this work, we propose an analytical solution for measuring similarity
Externí odkaz:
http://arxiv.org/abs/2310.04009
Degeneration in Nucleus basalis of Meynert signals earliest stage of Alzheimer’s disease progression
Publikováno v:
In Neurobiology of Aging July 2024 139:54-63
INTRODUCTION: Lateral ventricles are reliable and sensitive indicators of brain atrophy and disease progression in behavioral variant frontotemporal dementia (bvFTD). We aimed to investigate whether an automated tool using ventricular features could
Externí odkaz:
http://arxiv.org/abs/2103.03065
INTRODUCTION: Heterogeneity in the progression of Alzheimer's disease makes it challenging to predict the rate of cognitive and functional decline for individual patients. Tools for short-term prediction could help enrich clinical trial designs and f
Externí odkaz:
http://arxiv.org/abs/2101.08346
Autor:
Kersten-Oertel, Marta, Alamer, Ali, Fonov, Vladimir, Lo, Benjamin W. Y., Tampieri, Donatella, Collins, D. Louis
Stroke is the second leading cause of disability worldwide. In order to minimize disability, the goal of stroke treatment is to preserve tissue in the area where blood supply is decreased but sufficient to stave off cell death. Thrombectomy has been
Externí odkaz:
http://arxiv.org/abs/2001.07169
Autor:
Kuijf, Hugo J., Biesbroek, J. Matthijs, de Bresser, Jeroen, Heinen, Rutger, Andermatt, Simon, Bento, Mariana, Berseth, Matt, Belyaev, Mikhail, Cardoso, M. Jorge, Casamitjana, Adrià, Collins, D. Louis, Dadar, Mahsa, Georgiou, Achilleas, Ghafoorian, Mohsen, Jin, Dakai, Khademi, April, Knight, Jesse, Li, Hongwei, Lladó, Xavier, Luna, Miguel, Mahmood, Qaiser, McKinley, Richard, Mehrtash, Alireza, Ourselin, Sébastien, Park, Bo-yong, Park, Hyunjin, Park, Sang Hyun, Pezold, Simon, Puybareau, Elodie, Rittner, Leticia, Sudre, Carole H., Valverde, Sergi, Vilaplana, Verónica, Wiest, Roland, Xu, Yongchao, Xu, Ziyue, Zeng, Guodong, Zhang, Jianguo, Zheng, Guoyan, Chen, Christopher, van der Flier, Wiesje, Barkhof, Frederik, Viergever, Max A., Biessels, Geert Jan
Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are often still obtained from manual segmentations on brain MR images, whic
Externí odkaz:
http://arxiv.org/abs/1904.00682
Autor:
Giraud, Rémi, Ta, Vinh-Thong, Papadakis, Nicolas, Manjón, José V., Collins, D. Louis, Coupé, Pierrick, Initiative, Alzheimer's Disease Neuroimaging
Automatic segmentation methods are important tools for quantitative analysis of Magnetic Resonance Images (MRI). Recently, patch-based label fusion approaches have demonstrated state-of-the-art segmentation accuracy. In this paper, we introduce a new
Externí odkaz:
http://arxiv.org/abs/1903.07165
Neuroanatomical segmentation in magnetic resonance imaging (MRI) of the brain is a prerequisite for volume, thickness and shape measurements. This work introduces a new highly accurate and versatile method based on 3D convolutional neural networks fo
Externí odkaz:
http://arxiv.org/abs/1902.01478
Publikováno v:
In Neurobiology of Aging February 2023 122:112-119
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