El-Sayed H. Ibrahim1, Shannon Birchell2, Sherif Elfayoumy2
1Department of Radiology, University of Florida, Jacksonville, FL, United States; 2School of Computing, University of North Florida, Jacksonville, FL, United States
Manual segmentation of MRI images is inefficient and inconsistent method for measuring ventricular volumes. In this study, new artificial intelligence technique (ISITOAA) is developed and implemented for measuring ventricular volumes. The technique is based on automatic delineation of blood-myocardium border using ant colony optimization with salient isolated thresholding. The technique was implemented on datasets from eight volunteers and the results were compared to manual segmentation. ISITOAA provided both left and right ventricular segmentation in single processing, and provided stability measure of the solution. ISITOAA showed good agreement with the gold standard and was faster and more consistent than manual segmentation.