Longitudinal Automated Detection of White-Matter and Cortical Lesions in Relapsing-Remitting Multiple Sclerosis

Details

Serval ID
serval:BIB_60346FC75171
Type
Inproceedings: an article in a conference proceedings.
Publication sub-type
Abstract (Abstract): shot summary in a article that contain essentials elements presented during a scientific conference, lecture or from a poster.
Collection
Publications
Title
Longitudinal Automated Detection of White-Matter and Cortical Lesions in Relapsing-Remitting Multiple Sclerosis
Title of the conference
24th Proc. Intl. Soc. Mag. Reson. Med
Author(s)
Fartaria MJ., Bonnier G., Kober T., Roche A., Maréchal B., Rotzinger D., Schluep M., Du Pasquier R., Thiran JP., Krueger G., Meuli R., Bach Cuadra M., Granziera C.
Publication state
Published
Issued date
07/05/2016
Peer-reviewed
Oui
Language
english
Abstract
Magnetic Resonance Imaging(MRI) plays an important role for lesion assessment in early stages of Multiple Sclerosis(MS). This work aims at evaluating the performance of an automated tool for MS lesion detection, segmentation and tracking in longitudinal data, only for use in this research study. The method was tested with images acquired using both a "clinical" and an "advanced" imaging protocol for comparison. The validation was conducted in a cohort of thirty-two early MS patients through a ground truth obtained from manual segmentations by a neurologist and a radiologist. The use of the "advanced protocol" significantly improves lesion detection and classification in longitudinal analyses.
Create date
12/02/2018 16:45
Last modification date
21/08/2019 5:33
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