1 citations · 1 across the 4 of their papers we have counts for
13 papers · 1 filter
Resolution Meets Reduction: Efficient Visual Context for 3D Radiology Report Generation
Jonathan Suprijadi, Raphael Stock, Moritz Langenberg +10
Vision-language models offer a promising path toward automating radiology report generation, but applying them to full 3D CT volumes poses substantial computational challenges. Mod…
Primus: Enforcing Attention Usage for 3D Medical Image Segmentation
Tassilo Wald, Saikat Roy, Fabian Isensee +7
Transformers have achieved remarkable success across multiple fields, yet their impact on 3D medical image segmentation remains limited with convolutional networks still dominating…
Comprehensive language-image pre-training for 3D medical image understanding
Tassilo Wald, Ibrahim Ethem Hamamci, Yuan Gao +14
In the 3D medical image domain, vision-language pre-training is used to create vision-language encoders (VLEs) that can support radiologists by retrieving patients with similar abn…
An OpenMind for 3D medical vision self-supervised learning
Tassilo Wald, Constantin Ulrich, Jonathan Suprijadi +5
The field of self-supervised learning (SSL) for 3D medical images lacks consistency and standardization. While many methods have been developed, it is impossible to identify the cu…
Large Scale Supervised Pretraining For Traumatic Brain Injury Segmentation
Constantin Ulrich, Tassilo Wald, Fabian Isensee +1
The segmentation of lesions in Moderate to Severe Traumatic Brain Injury (msTBI) presents a significant challenge in neuroimaging due to the diverse characteristics of these lesion…
Revisiting MAE pre-training for 3D medical image segmentation
Tassilo Wald, Constantin Ulrich, Stanislav Lukyanenko +6
Self-Supervised Learning (SSL) presents an exciting opportunity to unlock the potential of vast, untapped clinical datasets, for various downstream applications that suffer from th…