LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset

Yiping Jiao, Jeroen Van Der Laak, Shadi Albarqouni, Zhang Li, Tao Tan, Abhir Bhalerao, Shenghua Cheng, Jiabo Ma, Johnathan Pocock, Josien P.W. Pluim, Navid Alemi Koohbanani, Raja Muhammad Saad Bashir, Shan E.Ahmed Raza, Sibo Liu, Simon Graham, Suzanne Wetstein, Syed Ali Khurram, Xiuli Liu, Nasir Rajpoot, Mitko VetaFrancesco Ciompi

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzhen (China). The competition required participants to automatically assess the number of lymphocytes, in particular T-cells, in images of colon, breast, and prostate cancer stained with CD3 and CD8 immunohistochemistry. Differently from other challenges setup in medical image analysis, LYSTO participants were solely given a few hours to address this problem. In this paper, we describe the goal and the multi-phase organization of the hackathon; we describe the proposed methods and the on-site results. Additionally, we present post-competition results where we show how the presented methods perform on an independent set of lung cancer slides, which was not part of the initial competition, as well as a comparison on lymphocyte assessment between presented methods and a panel of pathologists. We show that some of the participants were capable to achieve pathologist-level performance at lymphocyte assessment. After the hackathon, LYSTO was left as a lightweight plug-and-play benchmark dataset on grand-challenge website, together with an automatic evaluation platform.

Original languageEnglish
Pages (from-to)1161-1172
Number of pages12
JournalIEEE Journal of Biomedical and Health Informatics
Volume28
Issue number3
DOIs
Publication statusPublished - 1 Mar 2024

Keywords

  • Lymphocyte assessment
  • artificial intelligence
  • computational pathology
  • computer-aided diagnosis

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