Registration of Translated and Rotated Images Using Finite Fourier Transforms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation-based multilayer diagnosis lossless medical image compression
VIP '05 Proceedings of the Pan-Sydney area workshop on Visual information processing
Segmenting Brain Tumors using Alignment-Based Features
ICMLA '05 Proceedings of the Fourth International Conference on Machine Learning and Applications
Automatic detection of PET lesions
VIP '02 Selected papers from the 2002 Pan-Sydney workshop on Visualisation - Volume 22
Variational segmentation and PCA applied to dynamic PET analysis
VIP '02 Selected papers from the 2002 Pan-Sydney workshop on Visualisation - Volume 22
Medical Image Registration Based-on Points, Contour and Curves
BMEI '08 Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02
Automated segmentation of brain MR images
Pattern Recognition
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A contour-based approach to multisensor image registration
IEEE Transactions on Image Processing
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The aim of this work is to develop Computer Aided Diagnosis (CAD) system for the detection of brain tumor by using parallel implementation of ACO system for medical image segmentation applications due to the rapid execution for obtaining and extracting the Region of Interest (ROI) from the images for diagnostic purposes in medical field. For ROI segmentation, metaheuristic based Parallel Ant colony Optimization (PACO) approach has been implemented. The system has been simulated in the Mat lab for the parallel processing, using the master slave 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 in parallel. The computational results shows that parallel ACO systems uses the concept of the parallelization approach enabled the utilization of the intensity similarity measurement technique because of the capability of parallel processing. Medical image segmentation and detection at the early stage played vital roles for many health-related applications such as medical diagnostics, drug evaluation, medical research, training and teaching. Due to the rapid progress in the technologies for segmenting digital images for diagnostic purposes in medical field parallel Ant based CAD system are technologically feasible for Medical Domain which will certainly reduce the mortality rate.