A Light-Weight Interpretable Model for Nuclei Detection and Weakly-Supervised Segmentation

Yixiao Zhang, Adam Kortylewski, Qing Liu, Seyoun Park, Benjamin Green, Elizabeth Engle, Guillermo Almodovar, Ryan Walk, Sigfredo Soto-Diaz, Janis Taube, Alex Szalay, Alan Yuille

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

Abstract

The field of computational pathology has witnessed great advancements since deep neural networks have been widely applied. These networks usually require large numbers of annotated data to train vast parameters. However, it takes significant effort to annotate a large histo-pathology dataset. We introduce a light-weight and interpretable model for nuclei detection and weakly-supervised segmentation. It only requires annotations on isolated nucleus, rather than on all nuclei in the dataset. Besides, it is a generative compositional model that first locates parts of nucleus, then learns the spatial correlation of the parts to further locate the nucleus. This process brings interpretability in its prediction. Empirical results on an in-house dataset show that in detection, the proposed method achieved comparable or better performance than its deep network counterparts, especially when the annotated data is limited. It also outperforms popular weakly-supervised segmentation methods. The proposed method could be an alternative solution for the data-hungry problem of deep learning methods.

Original languageEnglish (US)
Title of host publicationMedical Optical Imaging and Virtual Microscopy Image Analysis - 1st International Workshop, MOVI 2022, Held in Conjunction with MICCAI 2022, Proceedings
EditorsYuankai Huo, Bryan A. Millis, Yuyin Zhou, Xiangxue Wang, Adam P. Harrison, Ziyue Xu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages145-155
Number of pages11
ISBN (Print)9783031169601
DOIs
StatePublished - 2022
Event1st International Workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis, MOVI 2022, held in conjunction with the 25th International Conference on Medical Imaging and Computer Assisted Intervention, MICCAI 2022 - Singapore, Singapore
Duration: Sep 18 2022Sep 18 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13578 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis, MOVI 2022, held in conjunction with the 25th International Conference on Medical Imaging and Computer Assisted Intervention, MICCAI 2022
Country/TerritorySingapore
CitySingapore
Period9/18/229/18/22

Keywords

  • Nuclei detection and segmentation
  • Weakly-supervised

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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