A Contrast-Adaptive Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis

Autor: Stefano Cerri, Hartwig R. Siebner, Jens Wuerfel, Mark Mühlau, Oula Puonti, Koen Van Leemput, Dominik Meier
Jazyk: angličtina
Rok vydání: 2020
Předmět:
FOS: Computer and information sciences
Computer Science - Machine Learning
Computer science
Computer Vision and Pattern Recognition (cs.CV)
Computer Science - Computer Vision and Pattern Recognition
Quantitative Biology - Quantitative Methods
Machine Learning (cs.LG)
0302 clinical medicine
Image Processing
Computer-Assisted
Contrast (vision)
Segmentation
Gray Matter
Quantitative Methods (q-bio.QM)
media_common
Lesion segmentation
Image and Video Processing (eess.IV)
05 social sciences
Brain
Magnetic Resonance Imaging
White Matter
ddc
Generative model
Neurology
Algorithms
Adaptive method
Cognitive Neuroscience
media_common.quotation_subject
White matter lesion
Neuroimaging
050105 experimental psychology
Article
lcsh:RC321-571
Multiple sclerosis
03 medical and health sciences
Image Interpretation
Computer-Assisted
FOS: Electrical engineering
electronic engineering
information engineering
medicine
Humans
0501 psychology and cognitive sciences
lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry
Whole-brain segmentation
business.industry
Pattern recognition
Electrical Engineering and Systems Science - Image and Video Processing
medicine.disease
Hyperintensity
FOS: Biological sciences
Artificial intelligence
Atrophy
business
030217 neurology & neurosurgery
Zdroj: Cerri, S, Puonti, O, Meier, D S, Wuerfel, J, Mühlau, M, Siebner, H R & Van Leemput, K 2020, ' A Contrast-Adaptive Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis ', NeuroImage, vol. 225, 117471 . https://doi.org/10.1016/j.neuroimage.2020.117471
NeuroImage, Vol 225, Iss, Pp 117471-(2021)
NeuroImage
Cerri, S, Puonti, O, Meier, D S, Wuerfel, J, Mühlau, M, Siebner, H R & Van Leemput, K 2021, ' A contrast-adaptive method for simultaneous whole-brain and lesion segmentation in multiple sclerosis ', NeuroImage, vol. 225, 117471 . https://doi.org/10.1016/j.neuroimage.2020.117471
DOI: 10.1016/j.neuroimage.2020.117471
Popis: Here we present a method for the simultaneous segmentation of white matter lesions and normal-appearing neuroanatomical structures from multi-contrast brain MRI scans of multiple sclerosis patients. The method integrates a novel model for white matter lesions into a previously validated generative model for whole-brain segmentation. By using separate models for the shape of anatomical structures and their appearance in MRI, the algorithm can adapt to data acquired with different scanners and imaging protocols without retraining. We validate the method using four disparate datasets, showing robust performance in white matter lesion segmentation while simultaneously segmenting dozens of other brain structures. We further demonstrate that the contrast-adaptive method can also be safely applied to MRI scans of healthy controls, and replicate previously documented atrophy patterns in deep gray matter structures in MS. The algorithm is publicly available as part of the open-source neuroimaging package FreeSurfer.
Databáze: OpenAIRE
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