Analysis of Mammogram for Detection of Micro-Calcification.

Date of Submission

December 2005

Date of Award

Winter 12-12-2006

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science


Electronics and Communication Sciences Unit (ECSU-Kolkata)


Pal, Nikhil Ranjan (ECSU-Kolkata; ISI)

Abstract (Summary of the Work)

With the recent westernization of our life style, the incidence rate of breast cancer is fast increasing in most of the part of the world, specifically in advanced countries. Primary prevention seems impossible since the causes of this disease still remain unknown. Early detection is the key to improving breast cancer prognosis. The presence of microcalcification clusters (MCCs) is an important sign for the detection of early breast carcinoma. Hence mammography is one of the reliable methods for early detection of breast carcinomas. In this thesis we develop methodologies for detection and classification of mammograms. In our mammogram analysis we shall use a neural network based method for feature selection and then use both neural networks and fuzzy rule based system for classification of micro-calcification. We have made some modification of an existing feature selection algorithm and also proposed a scheme for fuzzy rule extraction that avoids an important problem of existing fuzzy rule tuning methods.


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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


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