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Feature Extraction from Mammograms of Breast Cancer using Automatic Thresholding


Hiral Pokar , AITS, Rajkot, Gujarat; Prof. Poorvi H. Patel, AITS, Rajkot, Gujarat


Mammography, Segmentation, ROI (Region Of Interest), Micro-Calcification, Masses, Bilateral Asymmetry, Otsu’s Thresholding


Breast cancer detection is still complex and challenging problem. Diagnosis of cancer tissues in mammograms is a time consuming task even for highly skilled radiologists as it contains low signal to noise ratio and a complicated structured background. Therefore, in digital mammogram there is still a need to enhance imaging, where enhancement in medical imaging is the use of computers to make 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 scans the whole mammogram and performs filtering, segmentation, features extraction.

Other Details

Paper ID: IJSRDV3I31249
Published in: Volume : 3, Issue : 3
Publication Date: 01/06/2015
Page(s): 3267-3271

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