Colorectal cancer tissue classification using semi-supervised hypergraph convolutional network

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

7 Scopus citations

Abstract

Colorectal Cancer (CRC) is a leading cause of death around the globe, and therefore, the analysis of tumor micro environment in the CRC WSIs is important for the early detection of CRC. Conventional visual inspection is very time consuming and the process can undergo inaccuracies because of the subject-level assessment. Deep learning has shown promising results in medical image analysis. However, these approaches require a lot of labeling images from medical experts. In this paper, we propose a semi-supervised algorithm for CRC tissue classification. We propose to employ the hypergraph neural network to classify seven different biologically meaningful CRC tissue types. Firstly, image deep features are extracted from input patches using the pre-trained VGG19 model. The hypergraph is then constructed whereby patch-level deep features represent the vertices of hypergraph and hyperedges are assigned using pair-wise euclidean distance. The edges, vertices, and their corresponding patch-level features are passed through a feed-forward neural network to perform tissue classification in a transductive manner. Experiments are performed on an independent CRC tissue classification dataset and compared with existing state-of-the-art methods. Our results reveal that the proposed algorithm outperforms existing methods by achieving an overall accuracy of 95.46% and AvTP of 94.42%.

Original languageBritish English
Title of host publication2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021
PublisherIEEE Computer Society
Pages1306-1309
Number of pages4
ISBN (Electronic)9781665412469
DOIs
StatePublished - 13 Apr 2021
Event18th IEEE International Symposium on Biomedical Imaging, ISBI 2021 - Nice, France
Duration: 13 Apr 202116 Apr 2021

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2021-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference18th IEEE International Symposium on Biomedical Imaging, ISBI 2021
Country/TerritoryFrance
CityNice
Period13/04/2116/04/21

Keywords

  • Colorectal Cancer (CRC)
  • Deep Learning
  • Hypergraph Neural Network
  • Tissue Classification

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