Domain Adaptation of Digital Pathology Images using Joint Stain Color and Image Quality Constraints

Xi Long, Jingxin Liu*, Xianxu Hou

*Corresponding author for this work

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

Abstract

Digital pathology diagnosis systems face significant domain shift problems that hinder their performance on new datasets. Existing methods for aligning digital pathology images from different domains mainly focus on stain color and overlook the potential domain shifts caused by variations in image quality. To address this issue, we propose a novel parametric model that incorporates both stain color and image quality constraints for domain adaptation of digital pathology images. We evaluate our approach on the domain adaptive mitosis detection task through extensive experiments and ablation studies, showing that our method outperforms other state-of-the-art methods.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Image Processing (ICIP)
PublisherIEEE Computer Society
Pages1805-1809
Number of pages5
ISBN (Electronic)9781728198354
DOIs
Publication statusPublished - 2023
Event30th IEEE International Conference on Image Processing, ICIP 2023 - Kuala Lumpur, Malaysia
Duration: 8 Oct 202311 Oct 2023

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference30th IEEE International Conference on Image Processing, ICIP 2023
Country/TerritoryMalaysia
CityKuala Lumpur
Period8/10/2311/10/23

Keywords

  • digital pathology
  • domain adaptation
  • image quality
  • mitosis detection
  • stain color

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