Parallel Approach for Content Based Medical Image Retrieval System
- 1 ,
- 2 , Afganistan
Copyright: © 2020 M. Emmanuel, D.R. Ramesh Babu, Jayashree Jagdale, Pravin Game and G. P. Potdar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Problem statement: Parallel implementation of a CBIR system for medical applications due to the rapid progress in the technologies for obtaining and storing digital images for diagnostic purposes in medicine. Approach: For feature extraction Wavelet decomposition was used for texture, global color histograms for color and novel wavelet based approach for shape feature extraction. The system had been implemented in the Matlab, for the parallel processing, using the master slave approach the scheme was tested up to 16 hosts, Here parallelism is inherent in program loops, which focused on performing searching operation in parallel. Results: The experimental results showed that parallel CBIR systems were the need of the hour for evidence based medicine; the parallelization approach enabled the utilization of the similarity measurement technique because of the capability of parallel data processing in the several computers connected to the computational grid. Conclusion: Medical image retrieval 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 obtaining and storing digital images for diagnostic purposes in medicine and the rapid expansion of computer networks and the Internet, parallel CBIR systems are technologically feasible for Medical Domain and should be used in evidence based medicine.
- image retrieval
- medical image analysis