Implementation of Computer Aided Diagnosis System Based on Parallel Approach of Ant Based Medical Image Segmentation | Science Publications

Journal of Computer Science

Jayabalan Jaya¹  Keppanagowder Thanushkodi¹ 

关键词: Computer Aided Diagnosis (CAD);    Brain tissue;    CAD system;    skeletal systems;    interpret brain images;    Parallel Ant colony Optimization (PACO);    Region of Interest (ROI);    Non Rigid Registration Segmentation (NRRS);    Weighted Median (WM);   

DOI  :  10.3844/jcssp.2011.291.297

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

Problem statement: The aim of this study is to develop Computer Aided Diagnosis (CAD)system for the detection of brain tumor by using parallel implementation of ACO system for medicalimage segmentation applications due to the rapid execution for obtaining and extracting the Region ofInterest (ROI) from the images for diagnostic purposes in medical field. Approach: For ROIsegmentation, metaheuristic based Parallel Ant colony Optimization (PACO) approach has beenimplemented. The system has been simulated in the Mat lab for the parallel processing, using the masterslave approach and information exchange. The scheme is tested up to 10 real time MRI brain images.Here parallelism is inherent in program loops, which focused on performing searching operation inparallel. Results: The computational results shows that parallel ACO systems uses the concept of theparallelization approach enabled the utilization of the intensity similarity measurement technique becauseof the capability of parallel processing. Conclusion: Medical image segmentation and detection at theearly stage played vital roles for many health-related applications such as medical diagnostics, drugevaluation, medical research, training and teaching. Due to the rapid progress in the technologies forsegmenting digital images for diagnostic purposes in medical field parallel Ant based CAD system aretechnologically feasible for Medical Domain which will certainly reduce the mortality rate.

【 授权许可】

Unknown