A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development

  • Shiliang Ai
  • , Chen Li
  • , Xiaoyan Li
  • , Tao Jiang
  • , Marcin Grzegorzek
  • , Changhao Sun
  • , Md Mamunur Rahaman
  • , Jinghua Zhang
  • , Yudong Yao
  • , Hong Li

Research output: Contribution to journalReview articlepeer-review

36 Scopus citations

Abstract

Gastric cancer is a common and deadly cancer in the world. The gold standard for the detection of gastric cancer is the histological examination by pathologists, where Gastric Histopathological Image Analysis (GHIA) contributes significant diagnostic information. The histopathological images of gastric cancer contain sufficient characterization information, which plays a crucial role in the diagnosis and treatment of gastric cancer. In order to improve the accuracy and objectivity of GHIA, Computer-Aided Diagnosis (CAD) has been widely used in histological image analysis of gastric cancer. In this review, the CAD technique on pathological images of gastric cancer is summarized. Firstly, the paper summarizes the image preprocessing methods, then introduces the methods of feature extraction, and then generalizes the existing segmentation and classification techniques. Finally, these techniques are systematically introduced and analyzed for the convenience of future researchers.

Original languageEnglish
Article number6671417
JournalBioMed Research International
Volume2021
DOIs
StatePublished - 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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