24 citations · 66 across the 14 of their papers we have counts for
16 papers
Posterior temperature optimized Bayesian models for inverse problems in medical imaging
Max-Heinrich Laves, Malte Tölle, Alexander Schlaefer +1
We present Posterior Temperature Optimized Bayesian Inverse Models (POTOBIM), an unsupervised Bayesian approach to inverse problems in medical imaging using mean-field variational…
Unsupervised Anomaly Detection in 3D Brain MRI using Deep Learning with Multi-Task Brain Age Prediction
Marcel Bengs, Finn Behrendt, Max-Heinrich Laves +3
Lesion detection in brain Magnetic Resonance Images (MRIs) remains a challenging task. MRIs are typically read and interpreted by domain experts, which is a tedious and time-consum…
Robotic Tissue Sampling for Safe Post-mortem Biopsy in Infectious Corpses
Maximilian Neidhardt, Stefan Gerlach, Robin Mieling +12
In pathology and legal medicine, the histopathological and microbiological analysis of tissue samples from infected deceased is a valuable information for developing treatment stra…
Posterior Temperature Optimization in Variational Inference for Inverse Problems
Max-Heinrich Laves, Malte Tölle, Alexander Schlaefer +1
Bayesian methods feature useful properties for solving inverse problems, such as tomographic reconstruction. The prior distribution introduces regularization, which helps solving t…
Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging
Max-Heinrich Laves, Sontje Ihler, Jacob F. Fast +2
The consideration of predictive uncertainty in medical imaging with deep learning is of utmost importance. We apply estimation of both aleatoric and epistemic uncertainty by variat…
Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior
Max-Heinrich Laves, Malte Tölle, Tobias Ortmaier
Uncertainty quantification in inverse medical imaging tasks with deep learning has received little attention. However, deep models trained on large data sets tend to hallucinate an…