1 citations · 1 across the 5 of their papers we have counts for
5 papers
Intracranial Aneurysm Classification and Segmentation via Tri-Axial ROI and Multi-Task Learning
Pengcheng Shi, Kaiyuan Yang, Houjing Huang +7
Intracranial aneurysms are often asymptomatic until rupture, which carries high mortality. Rupture risk assessment and treatment planning depend on both aneurysm morphology and ana…
ProGiDiff: Prompt-Guided Diffusion-Based Medical Image Segmentation
Yuan Lin, Murong Xu, Marc Hölle +5
Widely adopted medical image segmentation methods, although efficient, are primarily deterministic and remain poorly amenable to natural language prompts. Thus, they lack the capab…
In search of truth: Evaluating concordance of AI-based anatomy segmentation models
Lena Giebeler, Deepa Krishnaswamy, David Clunie +9
Purpose AI-based methods for anatomy segmentation can help automate characterization of large imaging datasets. The growing number of similar in functionality models raises the cha…
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Murong Xu, Tamaz Amiranashvili, Fernando Navarro +30
Accurate delineation of anatomical structures in volumetric CT scans is crucial for diagnosis and treatment planning. While AI has advanced automated segmentation, current approach…
HALOS: Hallucination-free Organ Segmentation after Organ Resection Surgery
Anne-Marie Rickmann, Murong Xu, Tom Nuno Wolf +2
The wide range of research in deep learning-based medical image segmentation pushed the boundaries in a multitude of applications. A clinically relevant problem that received less…