Open AccessCOMPUTING THE EFFICIENCY OF IMAGE SEGMENTATION TECHNIQUES IN FMRI ANALYSIS
Author(s) -
C Arthi.,
. Savithri
Publication year - 2017
Publication title -
international journal of research - granthaalayah
Language(s) - English
Resource type - Journals
eISSN - 2394-3629
pISSN - 2350-0530
DOI - 10.29121/granthaalayah.v5.i3.2017.1772
Subject(s) - functional magnetic resonance imaging , computer science , artificial intelligence , segmentation , image processing , pattern recognition (psychology) , sample (material) , computer vision , image segmentation , image (mathematics) , psychology , neuroscience , chemistry , chromatography
Functional magnetic resonance imaging has become a very popular tool in neurological and medical analysis over the years. According to collated data, in the year 1993, as few as 20 papers were presented on the topic of fmri analysis; However, a decade later, as many as 1800 research papers talk about fmri analysis – an exponential increase. An analysis of the activated regions within the brain can be used to detect the its reactions to various stimuli with greater confidence compared to other methods but the success of accurately identifying brain stimuli however lies in the efficiency of the image processing algorithms applied to extract information from the fMRI scans. This paper analyzes the effectiveness of commonly used image processing algorithms in fMRI studies by statistically analyzing their effectiveness in extracting ROI’s in various images (sample size = 17) and tries to project the efficiency of these systems in fMRI scanning.