Improvement of Classification and Clustering of Images using Evolutionary Techniques
Vikas Gupta1, Rahul Malhotra2

1Vikas Gupta, Electronics and Communication, IKGPTU, Kapurthala, India.
2Rahul Malhotra, Electronics and Communication, IKGPTU, Kapurthala, India.

Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 1700-1703 | Volume-8 Issue-9, July 2019 | Retrieval Number: I8199078919/19©BEIESP | DOI: 10.35940/ijitee.I8199.078919
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Abstract: Segmentation of medical images is significant as it aids in mining the region of interest, such that the body part under analysis is extracted. Medical image segmentation helps in treatment of diseases, in surgeries and also aids in medical diagnosis. Various performance factors like Volumetric Overlap Error, Relative Volume Difference, Average Symmetric Surface Distance, Root Mean Square Symmetric Surface Distance, Maximum Symmetric Surface Distance. were evaluated which shows that outlier detection technique provides better results as compared to the implementation done without using this technique.
keyword: Computed Tomography (CT) Images, Segmentation, Outliers, E-ABC.

Scope of the Article: Classification