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Comparative Study of Heuristic-Based Support Vector Machine and Neural Network for Thermogram Breast Cancer Detection with Entropy Features

Comparative Study of Heuristic-Based Support Vector Machine and Neural Network for Thermogram Breast Cancer Detection with Entropy Features

Biomedical Engineering: Applications, Basis and Communications
Bhaveshkumar Dharmani
Abstract
Thermography is a noncontact, noninvasive imaging technology that is commonly utilized in the medical profession. As early identification of cancer is critical, the computer-assisted method can enhance the diagnosis rate, curing, and survival of cancer patients. Early diagnosis is one of the major essential steps in decreasing the health and socioeconomic consequences of this condition, given the high cost of therapy and the large prevalence of afflicted people. Mammography is currently the majorly utilized procedure for detecting breast cancer. Yet, owing to the low contrast that occurs from a thick breast, mammography is not advised for young women, and alternate methods must be investigated. This work plans to develop a comparative evaluation of two well-performing heuristic-based expert systems for detecting thermogram breast cancer. The thermogram images are taken from the standard DMR dataset. Then, the given images are transferred to the pre-processing stage. Here, the input ...

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