Michael Bidollahkhany - Graduate Student of Artificial intelligence and Robotics, K. N. Toosi University of Technology, Tehran, Iran

The goal of this paper is to investigate new methods of tumor progress study using machine vision, image processing andparallel programming techniques and proposing a solution to boost performance of magnetic resonance images differentialdetection that supports large scale medical image processing systems in determining the activity of tumors. After detectionthe tumor, we need to watch it out and log any activity and measuring rate of the tumor, growth, scattering, even decline andeliminating progresses. Following method can make it possible to compress the records of patient s MR or CT scan imagesand help physician and medics to scan every progress of tumor or even septicity s area, thus detect the result of efficiency oftreatment. Now by use of parallel programming and using modern graphic processing units we re able to do this processingsteps rapidly and apply this method on huge amounts of medical images, network based or by a personal computer.

Medical image processing, Parallel Algorithms, Information Retrieval, Edge detection, Tumor study