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A Review on Different Techniques Used for Feature Extractions from Mammogram of Breast Cancer

Hiral N. Pokar, Poorvi H. Patel


Breast cancer detection is still a complex and challenging problem. Mammogram contains low signal-to-noise ratio (SNR) and a complex structured background so identifying cancer tissues using this technique is a time consuming task even for expert radiologists. Therefore, there is still a need to enhance imaging in digital mammogram, where enhancement in medical imaging is the use of computers to make the image clearer. Studies show that relying on pure naked-eye observation of experts to detect such diseases can be prohibitively slow and inaccurate in some cases. Providing automatic, fast, and accurate image processing and artificial intelligence-based solutions for that task can be of great realistic significance. This paper discusses about different techniques used to scan the whole mammogram and perform filtering, segmentation, and features extraction.


Mammography, image enhancement, segmentation, Region of Interest (ROI), Microcalcification

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