From the 1 of 7 linked papers with an AI index.
7 papers
Longitudinal Multi-View Breast Cancer Risk Prediction
Solveig Thrun, Zijun Sun, Suaiba A. Salahuddin +5
The paper introduces LMV-Net, a deep learning model that jointly analyzes CC and MLO mammography views with explicit longitudinal alignment to improve breast cancer risk prediction…
Optimizing Data Augmentation through Bayesian Model Selection
Madi Matymov, Ba-Hien Tran, Michael Kampffmeyer +2
Data Augmentation (DA) has become an essential tool to improve robustness and generalization of modern machine learning. However, when deciding on DA strategies it is critical to c…
Tied Prototype Model for Few-Shot Medical Image Segmentation
Hyeongji Kim, Stine Hansen, Michael Kampffmeyer
Common prototype-based medical image few-shot segmentation (FSS) methods model foreground and background classes using class-specific prototypes. However, given the high variabilit…
EnLVAM: Enhanced Left Ventricle Linear Measurements Utilizing Anatomical Motion Mode
Durgesh K. Singh, Ahcene Boubekki, Qing Cao +3
Linear measurements of the left ventricle (LV) in the Parasternal Long Axis (PLAX) view using B-mode echocardiography are crucial for cardiac assessment. These involve placing 4-6…
Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
Solveig Thrun, Stine Hansen, Zijun Sun +7
Regular mammography screening is essential for early breast cancer detection. Deep learning-based risk prediction methods have sparked interest to adjust screening intervals for hi…
VMRA-MaR: An Asymmetry-Aware Temporal Framework for Longitudinal Breast Cancer Risk Prediction
Zijun Sun, Solveig Thrun, Michael Kampffmeyer
Breast cancer remains a leading cause of mortality worldwide and is typically detected via screening programs where healthy people are invited in regular intervals. Automated risk…