Event Title
Assessing Tissue Characterization of Abdominal Organs using Fuzzy C-Means cluster analysis of MRI images
Location
Georgia Campus
Start Date
1-5-2013 2:00 PM
End Date
1-5-2013 4:00 PM
Description
Abstract: Color fusion MRI is being investigated for its value in automatic segmentation of tissues. An existing color fusion MRI data set of the liver, pancreas, and kidney of a normal male volunteer was analyzed both visually and statistically. Automatic tissue segmentation can allow better differentiation of abdominal pathologies, as well as pathologies associated with other organs. My research hypothesis is that fuzzy c-means clustering can be used to quantify the confidence levels of correct classification of renal, pancreatic, and hepatic tissues visualized by the color fusion MRI method. Results from data show that fuzzy c-means clustering can be used to validate the correctness of classification of abdominal tissues that are visualized by color fusion MRI.
Assessing Tissue Characterization of Abdominal Organs using Fuzzy C-Means cluster analysis of MRI images
Georgia Campus
Abstract: Color fusion MRI is being investigated for its value in automatic segmentation of tissues. An existing color fusion MRI data set of the liver, pancreas, and kidney of a normal male volunteer was analyzed both visually and statistically. Automatic tissue segmentation can allow better differentiation of abdominal pathologies, as well as pathologies associated with other organs. My research hypothesis is that fuzzy c-means clustering can be used to quantify the confidence levels of correct classification of renal, pancreatic, and hepatic tissues visualized by the color fusion MRI method. Results from data show that fuzzy c-means clustering can be used to validate the correctness of classification of abdominal tissues that are visualized by color fusion MRI.