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