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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Published on: August 30, 2013
[Self-supervised classification method for breast pathology images fusing geometric priors and multi-scale
Liang Jiang1, Hui Cao1, Yongqi Nie2
1School of Medical Information Engineering, Shandong University of Traditional Chinese Medicine, Jinan 250355, P. R. China.
Summary
This study introduces IAM-BYOL, a self-supervised learning model for breast whole slide image analysis. It enhances diagnostic accuracy by incorporating geometric priors, improving robustness against rotation and scale variations in pathological images.
Area of Science:
- Computational pathology
- Medical image analysis
- Artificial intelligence in oncology