Automated Detection and Characterization of Multiple Sclerosis Lesions in Brain MR Images

1998 ◽  
Vol 16 (3) ◽  
pp. 311-318 ◽  
Author(s):  
D Goldberg-Zimring ◽  
A Achiron ◽  
S Miron ◽  
M Faibel ◽  
H Azhari
Keyword(s):  
Multiple Sclerosis ◽  
Automated Detection ◽  
Mr Images ◽  
Brain Mr Images

scholarly journals Lesions Detection of Multiple Sclerosis in 3D Brian MR Images by Using Artificial Immune Systems and Support Vector Machines

2021 ◽  
Vol 15 (2) ◽  
pp. 97-110
Author(s):  
Amina Merzoug ◽  
Nacéra Benamrane ◽  
Abdelmalik Taleb-Ahmed
Keyword(s):  
Multiple Sclerosis ◽  
Support Vector Machines ◽  
Brain Mri ◽  
Artificial Immune Systems ◽  
Support Vector ◽  
Mr Images ◽  
Artificial Immune ◽  
Immune Systems ◽  
Vector Machines ◽  
Brain Mr Images

This paper presents a segmentation method to detect multiple sclerosis (MS) lesions in brain MRI based on the artificial immune systems (AIS) and a support vector machines (SVM). In the first step, AIS is used to segment the three main brain tissues white matter, gray matter, and cerebrospinal fluid. Then the features were extracted and SVM is applied to detect the multiple sclerosis lesions based on SMO training algorithm. The experiments conducted on 3D brain MR images produce satisfying results.

scholarly journals An Automated Detection of Lacunar Infarct Regions in Brain MR Images : Preliminary Study

2002 ◽  
Vol 58 (3) ◽  
pp. 399-405 ◽  
Author(s):  
RYUJIRO YOKOYAMA ◽  
YONGBUM LEE ◽  
TAKESHI HARA ◽  
HIROSHI FUJITA ◽  
TAKAHIKO ASANO ◽  
...  
Keyword(s):  
Automated Detection ◽  
Lacunar Infarct ◽  
Mr Images ◽  
Preliminary Study ◽  
Brain Mr Images

ANALYSIS OF ANATOMICAL REGIONS IN ALZHEIMER'S BRAIN MR IMAGES USING LEVEL SETS AND MINKOWSKI FUNCTIONALS

2015 ◽  
Vol 15 (02) ◽  
pp. 1540024 ◽  
Author(s):  
M. KAYALVIZHI ◽  
K. R. ANANDH ◽  
G. KAVITHA ◽  
C. M. SUJATHA ◽  
S. RAMAKRISHNAN
Keyword(s):  
Level Set ◽  
Reaction Diffusion ◽  
Brain Structures ◽  
Mr Images ◽  
Minkowski Functionals ◽  
Discrimination Capability ◽  
Exact Boundary ◽  
Brain Mr Images ◽  
State Examination

In this work, an attempt is made to analyze anatomical regions of Alzheimer's brain MR images using level set and Minkowski functionals (MFs). The T1 weighted sagittal view of normal and abnormal images considered in this work, are obtained from MIRIAD database. The ventricle along with the hippocampus is segmented using Reaction Diffusion (RD) level set method and is subjected to further analysis using MFs. The prominent feature derived from the segmented region which contains ventricle and hippocampus is correlated with the Mini-Mental State Examination (MMSE) score. Results show that RD method is able to delineate the exact boundary of the ventricle along with hippocampus. It is observed that the MF-area of segmented region provides better discrimination of normal and abnormal subjects (p < 0.001) compared to the MF-perimeter and MF-Euler number. The correlation of the MMSE with prominent MF-area for normal, mild, moderate and severe are found to be 0.71, 0.82, 0.84 and 0.89, respectively. This suggests that characterization of brain structures using MFs improve the discrimination capability of brain disorders. Hence MF-area feature could be used for the study of progression in Alzheimer's disease (AD) like neurodegenerative disorders.

Axial vs Sagittal T2-Weighted Brain MR Images in the Evaluation of Multiple Sclerosis

1991 ◽  
Vol 15 (3) ◽  
pp. 359-364 ◽  
Author(s):  
Guy Wilms ◽  
Guy Marchal ◽  
Eric Kersschot ◽  
Piet Vanhoenacker ◽  
Philippe Demaerel ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Mr Images ◽  
Brain Mr Images
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