Vectorized persistent homology representations for characterizing glandular architecture in histology images

Deepak Roy Chittajallu, Neal Siekierski, Sanghoon Lee, Samuel Gerber, Jonathan Beezley, David Manthey, David Gutman, Lee Alex Donald Cooper

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

3 Scopus citations

Abstract

Characterizing glandular architecture in histology images of adenocarcinomas is a fundamental problem in digital pathology, with important implications for computer-assisted diagnosis and grading. In this paper, we present a new set of features for encoding the glandular epithelium architecture based on two recently developed vectorized persistent homology representations called persistence images and persistence landscapes and demonstrate their application to colorectal cancer diagnosis. On the MICCAI2015 Gland Segmentation Challenge Contest dataset with 165 images (85 training, 80 test images), we obtained a benign vs malignant classification accuracy of 85% and 83% using persistence image and persistence landscape based features, respectively.

Original languageEnglish (US)
Title of host publication2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018
PublisherIEEE Computer Society
Pages232-235
Number of pages4
ISBN (Electronic)9781538636367
DOIs
StatePublished - May 23 2018
Event15th IEEE International Symposium on Biomedical Imaging, ISBI 2018 - Washington, United States
Duration: Apr 4 2018Apr 7 2018

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2018-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference15th IEEE International Symposium on Biomedical Imaging, ISBI 2018
CountryUnited States
CityWashington
Period4/4/184/7/18

Keywords

  • Cancer Grading
  • Computer aided diagnosis
  • Histopathology
  • Machine learning
  • Persistence images
  • Persistence landscapes
  • Persistent homology

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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