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Updated: Apr 10, 2026
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Published on: August 30, 2013
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Digital Enabled Diagnosis System for Mammogram Images Classification Using Machine Learning
1Assistant Professor (SI.Gr.), Dept. of CSE, Anna University Regional Campus, Madurai, India.
Clinical Anatomy (New York, N.Y.)
|April 9, 2026
Summary
This study introduces a novel digital diagnosis system for early breast cancer detection using mammograms. The proposed framework enhances image quality, accurately localizes tumors, and improves classification accuracy for malignant, benign, and normal breast conditions.
Area of Science:
- Medical Imaging
- Artificial Intelligence in Healthcare
- Oncology
Background:
- Breast cancer is a leading cause of mortality in women, necessitating improved early detection methods.
- Current mammography screening relies heavily on radiologists and faces challenges with image quality and classification accuracy.
- Existing diagnostic systems often exhibit high error rates, limited robustness, and poor performance on imbalanced datasets.