DigestPath: A benchmark dataset with challenge review for the pathological detection and segmentation of digestive-system

Qian Da, Xiaodi Huang, Zhongyu Li, Yanfei Zuo, Chenbin Zhang, Jingxin Liu, Wen Chen, Jiahui Li, Dou Xu, Zhiqiang Hu, Hongmei Yi, Yan Guo, Zhe Wang, Ling Chen, Li Zhang, Xianying He, Xiaofan Zhang, Ke Mei, Chuang Zhu, Weizeng LuLinlin Shen, Jun Shi, Jun Li, Sreehari S, Ganapathy Krishnamurthi, Jiangcheng Yang, Tiancheng Lin, Qingyu Song, Xuechen Liu, Simon Graham, Raja Muhammad Saad Bashir, Canqian Yang, Shaofei Qin, Xinmei Tian, Baocai Yin, Jie Zhao, Dimitris N. Metaxas, Hongsheng Li, Chaofu Wang, Shaoting Zhang

Research output: Journal PublicationReview articlepeer-review

Abstract

Examination of pathological images is the golden standard for diagnosing and screening many kinds of cancers. Multiple datasets, benchmarks, and challenges have been released in recent years, resulting in significant improvements in computer-aided diagnosis (CAD) of related diseases. However, few existing works focus on the digestive system. We released two well-annotated benchmark datasets and organized challenges for the digestive-system pathological cell detection and tissue segmentation, in conjunction with the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). This paper first introduces the two released datasets, i.e., signet ring cell detection and colonoscopy tissue segmentation, with the descriptions of data collection, annotation, and potential uses. We also report the set-up, evaluation metrics, and top-performing methods and results of two challenge tasks for cell detection and tissue segmentation. In particular, the challenge received 234 effective submissions from 32 participating teams, where top-performing teams developed advancing approaches and tools for the CAD of digestive pathology. To the best of our knowledge, these are the first released publicly available datasets with corresponding challenges for the digestive-system pathological detection and segmentation. The related datasets and results provide new opportunities for the research and application of digestive pathology.

Original languageEnglish
Article number102485
JournalMedical Image Analysis
Volume80
DOIs
Publication statusPublished - Aug 2022
Externally publishedYes

Keywords

  • Benchmark dataset
  • Cell detection
  • Digestive system cancer
  • Grand challenge
  • Tissue segmentation

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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