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Diameter-based pseudo labeling for pathological image segmentation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a semi-and-weak supervised pathological image segmentation method that effectively leverages the pre-recorded long-diameter information of a tumor in clinical as weak supervision. By leveraging the tumor diameter, the proposed method can accurately identify candidate tumor regions for pseudo-label selection. The accurate pseudo labels can improve the segmentation performance. The experimental results demonstrate the effectiveness of our method, which achieved the best performance among the comparative methods.

Original languageEnglish
Title of host publication46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350371499
DOIs
Publication statusPublished - 2024
Event46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024 - Orlando, United States
Duration: Jul 15 2024Jul 19 2024

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024
Country/TerritoryUnited States
CityOrlando
Period7/15/247/19/24

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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