Accelerating Learning Process for Medical Image Segmentation using Opposition-based Learning

In this project we will translate and test artificial intelligence techniques to segment medical images with the capability to perform more accurately than conventional methods. The technique is expected to largely eliminate tedious manual delineation of suspicious objects in medical images or, at least, significantly reduce the intensity and frequency of manual modifications traditionally preformed by radiologists.