Home|Journals|Articles by Year|Audio Abstracts
 

Research Article

EEO. 2020; 19(3): 4535-4541


Detection And Classification Of Tumour Using Image Processing And Machine Learning

D.PUSHGARA RANI, S.DEIVANAYAGI, KARTHIKEYAN. K, P.SHALINI.




Abstract

Tumours, or aberrant unregulated cell development in any body component, can put enormous pressure on the numerous nerves and blood vessels, causing irreversible damage to the body. The key to avoiding such compilations is early tumour diagnosis. Advanced machine learning and image processing techniques can be used to detect tumours. Image pre-processing, segmentation, and feature extraction are all stages of tumour identification. Pre-processing include applying multiple filters to the image and removing noise. Methods such as thresholding and region growth are used in segmentation. For the retrieved tumour, features such as contrast, skewness, and entropy are calculated. To identify the tumour as benign or malignant, various classifiers such as convolution neural networks and nave bayes are used.

Key words: Medical Images, MRI, Segmentation, Tumor, Classifications.






Full-text options


Share this Article


Online Article Submission
• ejmanager.com




ejPort - eJManager.com
Refer & Earn
JournalList
About BiblioMed
License Information
Terms & Conditions
Privacy Policy
Contact Us

The articles in Bibliomed are open access articles licensed under Creative Commons Attribution 4.0 International License (CC BY), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.