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eess.IV2026
GazeXPErT: An Expert Eye-tracking Dataset for Interpretable and Explainable AI in Oncologic FDG-PET/CT Scans
Joy T Wu, Daniel Beckmann, Sarah Miller +15
[18F]FDG-PET/CT is a cornerstone imaging modality for guiding oncology therapies, yet human expert shortages necessitate more efficient diagnostic aids. While standalone AI models…
eess.IV2024
Fair Evaluation of Federated Learning Algorithms for Automated Breast Density Classification: The Results of the 2022 ACR-NCI-NVIDIA Federated Learning Challenge
Kendall Schmidt, Benjamin Bearce, Ken Chang +21
The correct interpretation of breast density is important in the assessment of breast cancer risk. AI has been shown capable of accurately predicting breast density, however, due t…
eess.IV2024
IMIL: Interactive Medical Image Learning Framework
Adrit Rao, Andrea Fisher, Ken Chang +4
Data augmentations are widely used in training medical image deep learning models to increase the diversity and size of sparse datasets. However, commonly used augmentation techniq…