Paper Info
Title
Segmentation and volume quantification of MR Images for the detection and monitoring multiple sclerosis progression.
Abstract
Multiple Sclerosis (MS) lesions detection and disease's progression monitoring at the same time, play an important role. The purpose of this research is to demonstrate a method for detecting MS plaques and volume estimation from MR Images for monitoring the progression of the disease and the brain atrophy caused. In the proposed research, a clustering-based method is utilized in order to delineate MS plaques in brain, based on anatomical information, brain geometry and lesion features. In addition to volumetric information concerning lesions and whole brain volume, volume quantification is employed to estimate MS atrophy by measuring Brain Parenchymal Fraction (BPF). In the present study, Fluid Attenuated Inversion Recovery (FLAIR) images were utilized for the detection of MS lesions and BPF evaluation, while Tl-weighted MR Images utilized in volume estimation. 30 MS patients were included in a dataset consisted of 3D FLAIR and T1-weighted MR images in order to evaluate the proposed technique. MRI scans performed in two different clinical visits, a baseline and a visit after 6 months. The results extracted in segmentation of MS lesions in terms of sensitivity is 73.80 %. The BPF at baseline estimated to 0.82 ± 0.01, and at 1follow up, 0.83 ± 0.01. Finally, the brain volume loss between baseline and after 6 months is 0.4%.
Year
DOI
Venue
2022
10.1109/EMBC48229.2022.9871533
Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
DocType
Volume
ISSN
Conference
2022
2694-0604
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Styliani P Zelilidou100.34
Evanthia E Tripoliti201.01
Kostas I Vlachos300.34
Spyridon Konitsiotis400.68
Dimitrios I. Fotiadis504.39