Feature Extraction from Mammograms of Breast Cancer using Automatic Thresholding |
Author(s): |
| Hiral Pokar , AITS, Rajkot, Gujarat; Prof. Poorvi H. Patel, AITS, Rajkot, Gujarat |
Keywords: |
| Mammography, Segmentation, ROI (Region Of Interest), Micro-Calcification, Masses, Bilateral Asymmetry, Otsu’s Thresholding |
Abstract |
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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 |
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Paper ID: IJSRDV3I31249 Published in: Volume : 3, Issue : 3 Publication Date: 01/06/2015 Page(s): 3267-3271 |
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