FEATURE EXTRACTION OF COLON AND RECTUM CANCER FROM MRI IMAGES

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Published: Feb 23, 2018
DOI: https://doi.org/10.26483/ijarcs.v9i1.5333
Keywords:
Image Processing, Feature Selection, Feature Extraction, Statistical Parameters, Gabor, GLCM

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Ajay Supadu Patil
North Maharashtra University, Jalgaon
Nita Patil
R. Srivaramangai

Abstract

Feature extraction, the third major component plays a vital role on the final expected outcome of the application using digital image processing. Feature plays a very significant role in the area of digital image processing. The image feature detection and extraction are based on the colour, shape and texture feature categories. Colour feature refers to the presence of one of the colours either in RGB space (Red, Green, Blue colour model) or in HSxspace (Hue, Saturation, Value/Brightness model) in the particular area of interest. Especially in medical imaging, the internal parts will have a specific colour slightly varying in hue. When the scan modality provides a colour image, colour feature can be used for processing. The structure of the organs and its parts if visible clearly, then the shape parameter can be used for classification of images. The knowledge of the domain experts will enable to find the structure as what and where it is located. Similarity in shape will help in identifying the objects. Irrespective of colour and shape, texture parameter plays an important role in classification problems. In the absence of colour and shape, the only available feature is the textural features of the object. It looks into the properties related with intensity values of each pixel. This paper proposes the textural feature extraction techniques that best suits for retrieving the properties of colon and rectum cancer MRI images which can be further processed for classification.

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Vol. 9 No. 1 (2018): January-February 2018
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Author Biography

Ajay Supadu Patil, North Maharashtra University, Jalgaon

Associate Professor, School of Computer Sciences

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