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02/13/2023
A Comprehensive Study of Modern Architectures and Regularization Approaches on CheXpert5000
Computer aided diagnosis (CAD) has gained an increased amount of attenti...
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04/26/2021
Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging
The consideration of predictive uncertainty in medical imaging with deep...
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07/09/2020
Patient-Specific Domain Adaptation for Fast Optical Flow Based on Teacher-Student Knowledge Transfer
Fast motion feedback is crucial in computer-aided surgery (CAS) on movin...
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06/20/2020
Calibration of Model Uncertainty for Dropout Variational Inference
The model uncertainty obtained by variational Bayesian inference with Mo...
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09/30/2019
Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference
In this paper, well-calibrated model uncertainty is obtained by using te...
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08/02/2019
Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say "I don't know" for Ambiguous Cases
We evaluate two different methods for the integration of prediction unce...
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08/02/2019
Deformable Medical Image Registration Using a Randomly-Initialized CNN as Regularization Prior
We present deformable unsupervised medical image registration using a ra...
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03/23/2019