Adaptive Semi-supervised Segmentation of Brain Vessels with Ambiguous Labels

Fengming Lin, Yan Xia, Nishant Ravikumar, Qiongyao Liu, Michael MacRaild, Alejandro F. Frangi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Accurate segmentation of brain vessels is crucial for cerebrovascular disease diagnosis and treatment. However, existing methods face challenges in capturing small vessels and handling datasets that are partially or ambiguously annotated. In this paper, we propose an adaptive semi-supervised approach to address these challenges. Our approach incorporates innovative techniques including progressive semi-supervised learning, adaptative training strategy, and boundary enhancement. Experimental results on 3DRA datasets demonstrate the superiority of our method in terms of mesh-based segmentation metrics. By leveraging the partially and ambiguously labeled data, which only annotates the main vessels, our method achieves impressive segmentation performance on mislabeled fine vessels, showcasing its potential for clinical applications.

Original languageEnglish
Title of host publicationData Augmentation, Labelling, and Imperfections - 3rd MICCAI Workshop, DALI 2023 Held in Conjunction with MICCAI 2023, Proceedings
EditorsYuan Xue, Chen Chen, Chao Chen, Lianrui Zuo, Yihao Liu
PublisherSpringer Nature
Pages106-116
Number of pages11
ISBN (Print)9783031581700
DOIs
Publication statusPublished - 2024
Event3rd International Workshop on Data Augmentation, Labeling, and Imperfections, DALI 2023 in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2023 - Vancouver, Canada
Duration: 12 Oct 202312 Oct 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14379 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Data Augmentation, Labeling, and Imperfections, DALI 2023 in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2023
Country/TerritoryCanada
CityVancouver
Period12/10/2312/10/23

Keywords

  • Adaptive model
  • Brain vessel segmentation
  • Semi-supervised learning

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