• Christina Baby
• Teena Joseph

With the growth of technology, a lot of computer aided system has been developed for detecting the presence of disease with a significant emphasis on systems accuracy. The paper brings out different steps in computer-aided medical diagnosis with soft computing skills. This work concentrates on image classification task through the use of image spectral components. The spectral components within the image for each class are used for categorization. Particle swarm optimization (PSO) is applied to trim the fuzzy rules generated by a trained Hyper-Rectangular Composite Neural Networks to improve the recognition performance Case-Based Reasoning (CBR) process is also explored here and it is an approach for developing knowledge-based medical decision support system. This is the process of solving new problems based on the solutions of similar past problems.

Machine learning, Classification, Computer aided diagnosis, Transfer learning, Point-based registration, Registration error, Accuracy

"Machine Learning Approaches In Medical Image Analysis Using PSO Clustering: From Detection to Diagnosis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.283-287, May 2019, Available :http://www.jetir.org/papers/JETIRCV06057.pdf

"Machine Learning Approaches In Medical Image Analysis Using PSO Clustering: From Detection to Diagnosis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp283-287, May 2019, Available at : http://www.jetir.org/papers/JETIRCV06057.pdf