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on
1
Introduction
2
What is a mammogram
3
Challenges
4
Goals
5
Annotations
6
Segmentation
7
Patchwise Segmentation
8
Results
9
Semantic Segmentation
10
Dilated Convolution
11
Comparison
12
Patchwork Results
13
Quantification
14
Accuracy
15
BC Quantification
16
Evaluation
17
Conclusion
18
Question for Sophie
Description:
Explore a comprehensive lecture on the segmentation and quantification of breast arterial calcifications (BAC) in mammograms. Delve into the development of a lightweight fine vessel segmentation method called Simple Context U-Net (SCU-Net) for accurate BAC detection. Learn about five quantitative metrics proposed to measure BAC progression, including Sum of Mask Probability, Sum of Mask Area, and Sum of Mask Intensity. Discover how these metrics perform in longitudinal studies and compare to breast CT measurements. Gain insights into the potential of BAC measurements for personalized cardiovascular disease risk assessment in women.

Segmentation and Quantification of Breast Arterial Calcifications - Xiaoyuan Guo

Stanford University
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