6 papers · 1 filter
Explicitly Aligned Multi-View Breast Cancer Risk Prediction from Variable-Length Screening Histories
Solveig Thrun, Zijun Sun, Suaiba A. Salahuddin +5
Accurate breast cancer risk prediction from screening mammography is essential for improved risk stratification and personalized screening. It can benefit from both temporal breast…
Longitudinal Multi-View Breast Cancer Risk Prediction
Solveig Thrun, Zijun Sun, Suaiba A. Salahuddin +5
Accurate breast cancer risk prediction from screening mammography is critical for enabling personalized screening intervals and early detection. Recent deep learning methods have s…
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…
Robust Classification by Coupling Data Mollification with Label Smoothing
Markus Heinonen, Ba-Hien Tran, Michael Kampffmeyer +1
Introducing training-time augmentations is a key technique to enhance generalization and prepare deep neural networks against test-time corruptions. Inspired by the success of gene…
Forest Parameter Prediction by Multiobjective Deep Learning of Regression Models Trained with Pseudo-Target Imputation
Sara Björk, Stian N. Anfinsen, Michael Kampffmeyer +3
In prediction of forest parameters with data from remote sensing (RS), regression models have traditionally been trained on a small sample of ground reference data. This paper prop…