activity
20202025
most citedMedical Deep Learning -- A systematic Meta-Review

259 citations · 260 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Towards the Automatic Segmentation, Modeling and Meshing of the Aortic Vessel Tree from Multicenter Acquisitions: An Overview of the SEG.A. 2023 Segmentation of the Aorta Challenge

Yuan Jin, Antonio Pepe, Gian Marco Melito +36

The automated analysis of the aortic vessel tree (AVT) from computed tomography angiography (CTA) holds immense clinical potential, but its development has been impeded by a lack o…

eess.IV2024

Efficient MedSAMs: Segment Anything in Medical Images on Laptop

Jun Ma, Feifei Li, Sumin Kim +79

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive co…

cs.CV2024

Deep Medial Voxels: Learned Medial Axis Approximations for Anatomical Shape Modeling

Antonio Pepe, Richard Schussnig, Jianning Li +3

Shape reconstruction from imaging volumes is a recurring need in medical image analysis. Common workflows start with a segmentation step, followed by careful post-processing and,fi…

cs.CV2023★ 1 cited

DeepDR: Deep Structure-Aware RGB-D Inpainting for Diminished Reality

Christina Gsaxner, Shohei Mori, Dieter Schmalstieg +4

Diminished reality (DR) refers to the removal of real objects from the environment by virtually replacing them with their background. Modern DR frameworks use inpainting to halluci…

eess.IV2020★ 259 cited

Medical Deep Learning -- A systematic Meta-Review

Jan Egger, Christina Gsaxner, Antonio Pepe +5

Deep learning (DL) has remarkably impacted several different scientific disciplines over the last few years. E.g., in image processing and analysis, DL algorithms were able to outp…