Journal of the Korean Society of Systems Engineering (시스템엔지니어링학술지)

The Korean Society of Systems Engineering (한국시스템엔지니어링학회)
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User Interface Application for Cancer Classification using Histopathology Images

  • Naeem, Tayyaba (Research and Development Team, Humintec, Co. Ltd.) ;
  • Qamar, Shamweel (System Biomedical Informatics, Ajou University) ;
  • Park, Peom (Research and Development Team, Humintec, Co. Ltd.)
  • Received : 2021.10.18
  • Accepted : 2021.12.14
  • Published : 2021.12.31
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Abstract

User interface for cancer classification system is a software application with clinician's friendly tools and functions to diagnose cancer from pathology images. Pathology evolved from manual diagnosis to computer-aided diagnosis with the help of Artificial Intelligence tools and algorithms. In this paper, we explained each block of the project life cycle for the implementation of automated breast cancer classification software using AI and machine learning algorithms to classify normal and invasive breast histology images. The system was designed to help the pathologists in an automatic and efficient diagnosis of breast cancer. To design the classification model, Hematoxylin and Eosin (H&E) stained breast histology images were obtained from the ICIAR Breast Cancer challenge. These images are stain normalized to minimize the error that can occur during model training due to pathological stains. The normalized dataset was fed into the ResNet-34 for the classification of normal and invasive breast cancer images. ResNet-34 gave 94% accuracy, 93% F Score, 95% of model Recall, and 91% precision.

Keywords

Acknowledgement

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI18C0316)."

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