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Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images-The ACDC@LungHP Challenge 2019

  1. Author:
    Li, Zhang
    Zhang, Jiehua
    Tan, Tao
    Teng, Xichao
    Sun, Xiaoliang
    Zhao, Hong
    Liu, Lihong
    Xiao, Yang
    Lee, Byungjae
    Li, Yilong
    Zhang, Qianni
    Sun, Shujiao
    Zheng, Yushan
    Yan, Junyu
    Li, Ni
    Hong, Yiyu
    Ko, Junsu
    Jung,Hyun
    Liu,Yanling
    Chen, Yu-cheng
    Wang, Ching-wei
    Yurovskiy, Vladimir
    Maevskikh, Pavel
    Khanagha, Vahid
    Jiang, Yi
    Yu, Li
    Liu, Zhihong
    Li, Daiqiang
    Schueffler, Peter J.
    Yu, Qifeng
    Chen, Hui
    Tang, Yuling
    Litjens, Geert

  2. Author Address

    Natl Univ Def Technol, Coll Aerosp Sci & Engn, Changsha 410073, Peoples R China.Hunan Prov Key Lab Image Measurement & Vis Nav, Changsha, Peoples R China.Eindhoven Univ Technol, Dept Math & Comp Sci, NL-5600 MB Eindhoven, Netherlands.ScreenPoint Med, NL-6525 EC Nijmegen, Netherlands.Pingan Technol, Shenzhen 518000, Peoples R China.Lunit Inc, Seoul, South Korea.Queen Mary Univ London, Sch Elect Engn & Comp Sci, London, England.Beihang Univ, Image Proc Ctr, Sch Astronaut, Beijing 102206, Peoples R China.Beijing Adv Innovat Ctr Biomed Engn, Beijing 100191, Peoples R China.Beihang Univ, Beijing Adv Innovat Ctr Biomed Engn, Beijing 102206, Peoples R China.Image Proc Ctr, Beijing 102206, Peoples R China.Beihang Univ, Sch Astronaut, Beijing 102206, Peoples R China.Beihang Univ, Sch Astronaut, AstLab, Beijing 102206, Peoples R China.Arontier Co Ltd, R&D Ctr, Seoul, South Korea.Frederick Natl Lab, Frederick, MD USA.Natl Taiwan Univ Sci & Technol, Ctr Comp Vis & Med Imaging, Taipei, Taiwan.Natl Taiwan Univ Sci & Technol, Grad Inst Biomed Engn, Taipei, Taiwan.Natl Taiwan Univ Sci & Technol, Grad Inst Appl Sci & Technol, Taipei, Taiwan.AI Explore, Taipei, Taiwan.Res Dept Skychain Global, Ekaterinburg, Russia.Motorola Solut Inc Plantat, Audio Solut Team, Ft Lauderdale, FL USA.Cent South Univ, Xiangya Hosp 2, Changsha, Peoples R China.Lensee Biotechnol Co Ltd, Ningbo, Peoples R China.Cent South Univ, Hunan Canc Hosp, Changsha, Peoples R China.Mem Sloan Kettering Canc Ctr, New York, NY 10021 USA.First Hosp Changsha City, Changsha, Peoples R China.Radboud Univ Nijmegen, Med Ctr, Nijmegen, Netherlands.
    1. Year: 2021
    2. Date: Feb
  2. Journal: IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
  3. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC,
    1. 25
    2. 2
    3. Pages: 429-440
  5. Type of Article: Article
  6. ISSN: 2168-2194
  1. Abstract:

    Accurate segmentation of lung cancer in pathology slides is a critical step in improving patient care. We proposed the ACDC@LungHP (Automatic Cancer Detection and Classification in Whole-slide Lung Histopathology) challenge for evaluating different computer-aided diagnosis (CADs) methods on the automatic diagnosis of lung cancer. The ACDC@LungHP 2019 focused on segmentation (pixel-wise detection) of cancer tissue in whole slide imaging (WSI), using an annotated dataset of 150 training images and 50 test images from 200 patients. This paper reviews this challenge and summarizes the top 10 submitted methods for lung cancer segmentation. All methods were evaluated using metrics using the precision, accuracy, sensitivity, specificity, and DICE coefficient (DC). The DC ranged from 0.7354 +/- 0.1149 to 0.8372 +/- 0.0858. The DC of the best method was close to the inter-observer agreement (0.8398 +/- 0.0890). All methods were based on deep learning and categorized into two groups: multi-model method and single model method. In general, multi-model methods were significantly better (p< 0.01) than single model methods, with mean DC of 0.7966 and 0.7544, respectively. Deep learning based methods could potentially help pathologists find suspicious regions for further analysis of lung cancer in WSI.

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External Sources

  1. View Full Text
  2. DOI: 10.1109/JBHI.2020.3039741
  3. PMID: 33216724
  4. View record in Web of Science®
  5. WOS: 000616310200013

Library Notes

  1. Fiscal Year: FY2020-2021
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