activity
20232026
most citedThe TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

14 citations · 22 across the 11 of their papers we have counts for

collaborators

13 papers

cs.CV2026

Anguinus Sculpturae: Compositional Synthesis of Peak-Enhancement Breast DCE-MRI Scans

Benjamin Hamm, Nico Albert Disch, Maximilian Rokuss +3

Dynamic contrast-enhanced breast MRI (DCE-MRI) is rich in anatomical and perfusion information, but its reliance on gadolinium-based contrast agents raises safety concerns and adds…

cs.CV2026

Feature Space Guidance for Breast Cancer Classification in DCE-MRI

Benjamin Hamm, Yannick Kirchhoff, Maximilian Rokuss +6

Dynamic contrast enhanced breast MRI (DCE-MRI) is a powerful clinical tool for breast cancer detection, providing high resolution anatomical detail together with rich temporal cont…

eess.IV2026

GLOW-FDG: Generalized cancer LesiOn Whole-body segmentation model for F-FDG-PET/CT

Maksym Fritsak, Maximilian Rokuss, Hubert S. Gabryś +10

Whole-body fluorodeoxyglucose positron emission tomography combined with computed tomography is widely used in cancer care, but manual lesion delineation is slow, subjective, and d…

cs.CV2026

Exploiting Longitudinal Context in Clinician-Verified Interactive Lesion Tracking

Yannick Kirchhoff, Maximilian Rokuss, Daniel Philipp Mertens +5

Tracking tumor lesions across serial CT scans is essential for oncological response assessment. Existing automated methods face a fundamental trade-off: end-to-end trackers achieve…

cs.CV2025

VoxTell: Free-Text Promptable Universal 3D Medical Image Segmentation

Maximilian Rokuss, Moritz Langenberg, Yannick Kirchhoff +8

We introduce VoxTell, a vision-language model for text-prompted volumetric medical image segmentation. It maps free-form descriptions, from single words to full clinical sentences,…

eess.IV2025

Promptable Longitudinal Lesion Segmentation in Whole-Body CT

Yannick Kirchhoff, Maximilian Rokuss, Fabian Isensee +1

Accurate segmentation of lesions in longitudinal whole-body CT is essential for monitoring disease progression and treatment response. While automated methods benefit from incorpor…

cs.CV2025★ 1 cited

Automated segmentation of pediatric neuroblastoma on multi-modal MRI: Results of the SPPIN challenge at MICCAI 2023

M. A. D. Buser, D. C. Simons, M. Fitski +27

Surgery plays an important role within the treatment for neuroblastoma, a common pediatric cancer. This requires careful planning, often via magnetic resonance imaging (MRI)-based…

cs.CV2025★ 2 cited

LesionLocator: Zero-Shot Universal Tumor Segmentation and Tracking in 3D Whole-Body Imaging

Maximilian Rokuss, Yannick Kirchhoff, Seval Akbal +7

In this work, we present LesionLocator, a framework for zero-shot longitudinal lesion tracking and segmentation in 3D medical imaging, establishing the first end-to-end model capab…

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…

cs.CV2025

Expectation-Maximization as the Engine of Scalable Medical Intelligence

Wenxuan Li, Pedro R. A. S. Bassi, Tianyu Lin +19

Large, high-quality, annotated datasets are the foundation of medical AI research, but constructing even a small, moderate-quality, annotated dataset can take years of effort from…

cs.CV2024★ 1 cited

Scaling nnU-Net for CBCT Segmentation

Fabian Isensee, Yannick Kirchhoff, Lars Kraemer +3

This paper presents our approach to scaling the nnU-Net framework for multi-structure segmentation on Cone Beam Computed Tomography (CBCT) images, specifically in the scope of the…

cs.CV2024★ 2 cited

Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?

Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50

How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…

cs.CV2023★ 14 cited

The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

Kaiyuan Yang, Fabio Musio, Yihui Ma +112

The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to influence the risk, severity, an…