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20192026
most citedGadolinium dose reduction for brain MRI using conditional deep learning

3 citations · 3 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

Test-Time Adaptation in Optical Coherence Tomography Using Trajectory-Aligned Time-Independent Flow

Veit Hucke, Thomas Pinetz, Gregor Reiter +2

Optical coherence tomography (OCT) is essential in ophthalmology, but inconsistent image quality especially in low-cost devices hinders automated analysis. To address this, we intr…

cs.CV2026

Quantification of Uncertainty with Adversarial Models in Medical Image Segmentation

Hana Jebril, Thomas Pinetz, Günter Klambauer +1

Reliable pixel-level uncertainty quantification holds the potential to transform clinical workflows by enabling high-fidelity longitudinal monitoring and distinguishing true pathol…

cs.CV2026

Exploiting Intermediate Reconstructions in Optical Coherence Tomography for Test-Time Adaption of Medical Image Segmentation

Thomas Pinetz, Veit Hucke, Hrvoje Bogunovic

Primary health care frequently relies on low-cost imaging devices, which are commonly used for screening purposes. To ensure accurate diagnosis, these systems depend on advanced re…

cs.CV2025

GARD: Gamma-based Anatomical Restoration and Denoising for Retinal OCT

Botond Fazekas, Thomas Pinetz, Guilherme Aresta +2

Optical Coherence Tomography (OCT) is a vital imaging modality for diagnosing and monitoring retinal diseases. However, OCT images are inherently degraded by speckle noise, which o…

cs.CV2020

Shared Prior Learning of Energy-Based Models for Image Reconstruction

Thomas Pinetz, Erich Kobler, Thomas Pock +1

We propose a novel learning-based framework for image reconstruction particularly designed for training without ground truth data, which has three major building blocks: energy-bas…