activity
20222024
most citedUnleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the FLARE22 Challenge

19 citations · 23 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20241 cited

AdaptDiff: Cross-Modality Domain Adaptation via Weak Conditional Semantic Diffusion for Retinal Vessel Segmentation

Dewei Hu, Hao Li, Han Liu +4

Deep learning has shown remarkable performance in medical image segmentation. However, despite its promise, deep learning has many challenges in practice due to its inability to ef…

cs.CV20231 cited

Assessing Test-time Variability for Interactive 3D Medical Image Segmentation with Diverse Point Prompts

Hao Li, Han Liu, Dewei Hu +2

Interactive segmentation model leverages prompts from users to produce robust segmentation. This advancement is facilitated by prompt engineering, where interactive prompts serve a…

cs.CV2023

MAP: Domain Generalization via Meta-Learning on Anatomy-Consistent Pseudo-Modalities

Dewei Hu, Hao Li, Han Liu +3

Deep models suffer from limited generalization capability to unseen domains, which has severely hindered their clinical applicability. Specifically for the retinal vessel segmentat…

cs.CV2023

VesselMorph: Domain-Generalized Retinal Vessel Segmentation via Shape-Aware Representation

Dewei Hu, Hao Li, Han Liu +3

Due to the absence of a single standardized imaging protocol, domain shift between data acquired from different sites is an inherent property of medical images and has become a maj…

eess.IV202319 cited

Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the FLARE22 Challenge

Jun Ma, Yao Zhang, Song Gu +26

Quantitative organ assessment is an essential step in automated abdominal disease diagnosis and treatment planning. Artificial intelligence (AI) has shown great potential to automa…

eess.IV20231 cited

Self-Supervised CSF Inpainting with Synthetic Atrophy for Improved Accuracy Validation of Cortical Surface Analyses

Jiacheng Wang, Kathleen E. Larson, Ipek Oguz

Accuracy validation of cortical thickness measurement is a difficult problem due to the lack of ground truth data. To address this need, many methods have been developed to synthet…