activity
20182026
most citedA large annotated medical image dataset for the development and evaluation of segmentation algorithms

718 citations · 731 across the 7 of their papers we have counts for

collaborators
Showing cs.CVShow all

10 papers · 1 filter

cs.CV2026

Designing UNICORN: a Unified Benchmark for Imaging in Computational Pathology, Radiology, and Natural Language

Michelle Stegeman, Lena Philipp, Fennie van der Graaf +19

Medical foundation models show promise to learn broadly generalizable features from large, diverse datasets. This could be the base for reliable cross-modality generalization and r…

cs.CV2025

Divide to Conquer: A Field Decomposition Approach for Multi-Organ Whole-Body CT Image Registration

Xuan Loc Pham, Mathias Prokop, Bram van Ginneken +1

Image registration is an essential technique for the analysis of Computed Tomography (CT) images in clinical practice. However, existing methodologies are predominantly tailored to…

cs.CV2025

In the Picture: Medical Imaging Datasets, Artifacts, and their Living Review

Amelia Jiménez-Sánchez, Natalia-Rozalia Avlona, Sarah de Boer +26

Datasets play a critical role in medical imaging research, yet issues such as label quality, shortcuts, and metadata are often overlooked. This lack of attention may harm the gener…

cs.CV20224 cited

Structure and position-aware graph neural network for airway labeling

Weiyi Xie, Colin Jacobs, Jean-Paul Charbonnier +1

We present a novel graph-based approach for labeling the anatomical branches of a given airway tree segmentation. The proposed method formulates airway labeling as a branch classif…

cs.CV2020

A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises

S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos +6

Since its renaissance, deep learning has been widely used in various medical imaging tasks and has achieved remarkable success in many medical imaging applications, thereby propell…

cs.CV2019

mlVIRNET: Multilevel Variational Image Registration Network

Alessa Hering, Bram van Ginneken, Stefan Heldmann

We present a novel multilevel approach for deep learning based image registration. Recently published deep learning based registration methods have shown promising results for a wi…