activity
20242026
most citedLeveraging Foundation Models for Content-Based Image Retrieval in Radiology

5 citations · 10 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

nnFoundation: 3D Foundation Models for Radiology

Constantin Ulrich Harsy, Tassilo Wald, Karol Gotkowski +80

Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shift. Foundation models promise…

cs.CV2026

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…

cs.CV2025★ 1 cited

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…

eess.IV2025★ 2 cited

Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound: The TDSC-ABUS Challenge

Gongning Luo, Mingwang Xu, Hongyu Chen +34

Breast cancer is one of the most common causes of death among women worldwide. Early detection helps in reducing the number of deaths. Automated 3D Breast Ultrasound (ABUS) is a ne…

eess.IV2024

PSFHS Challenge Report: Pubic Symphysis and Fetal Head Segmentation from Intrapartum Ultrasound Images

Jieyun Bai, Zihao Zhou, Zhanhong Ou +26

Segmentation of the fetal and maternal structures, particularly intrapartum ultrasound imaging as advocated by the International Society of Ultrasound in Obstetrics and Gynecology…

cs.CV2024★ 2 cited

Visual Prompt Engineering for Vision Language Models in Radiology

Stefan Denner, Markus Bujotzek, Dimitrios Bounias +3

Medical image classification plays a crucial role in clinical decision-making, yet most models are constrained to a fixed set of predefined classes, limiting their adaptability to…

cs.CV2024★ 5 cited

Leveraging Foundation Models for Content-Based Image Retrieval in Radiology

Stefan Denner, David Zimmerer, Dimitrios Bounias +8

Content-based image retrieval (CBIR) has the potential to significantly improve diagnostic aid and medical research in radiology. However, current CBIR systems face limitations due…