Robust segmentation of nucleus in histopathology images via mask R-CNN

Xinpeng Xie, Yuexiang Li, Menglu Zhang, Linlin Shen

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

10 Citations (Scopus)

Abstract

Nuclei segmentation plays an import role in histopathology images analysis. Deep learning approaches have shown its strength for histopathology images processing in various studies. In this paper, we proposed a novel deep learning framework for automatic nuclei segmentation. The framework adopts the Mask R-CNN as backbone and employs structure-preserving color normalization (SPCN) and watershed for pre- and post-processing. The proposed framework achieved a Dice score of 90.46% on the validation set, which demonstrates its competing segmentation performance.

Original languageEnglish
Title of host publicationBrainlesion
Subtitle of host publicationGlioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers
EditorsFarahani Keyvan, Alessandro Crimi, Spyridon Bakas, Mauricio Reyes, Theo van Walsum, Hugo Kuijf
PublisherSpringer Verlag
Pages428-436
Number of pages9
ISBN (Print)9783030117221
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event4th International MICCAI Brainlesion Workshop, BrainLes 2018 held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2018 - Granada, Spain
Duration: 16 Sep 201820 Sep 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11383 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International MICCAI Brainlesion Workshop, BrainLes 2018 held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2018
Country/TerritorySpain
CityGranada
Period16/09/1820/09/18

Keywords

  • Deep learning
  • Instance segmentation
  • Nuclei segmentation
  • SPCN

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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