We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzen (China). The competition required participants to automatically assess the number of lymphocytes, in particular T-cells, in histopathological 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. LYSTO has supported a number of research in lymphocyte assessment in oncology. LYSTO will be a long-lasting educational challenge for deep learning and digital pathology, it is available at https://lysto.grand-challenge.org/.

翻译：我们介绍LYSTO，即淋巴细胞评估黑客马拉松，该赛事与2019年中国深圳举办的MICCAI会议同期举行。竞赛要求参与者自动评估经CD3和CD8免疫组化染色的结肠癌、乳腺癌和前列腺癌组织病理学图像中淋巴细胞（特别是T细胞）的数量。与医学图像分析领域的其他挑战不同，LYSTO参与者仅有数小时时间解决此问题。本文描述了该黑客马拉松的目标和多阶段组织过程；我们介绍了所提出的方法及现场结果。此外，我们展示了赛后结果，包括这些方法在独立肺癌切片（非初始竞赛部分）上的表现，以及所提方法与病理学家小组在淋巴细胞评估上的对比。研究表明，部分参与者能够在淋巴细胞评估中达到病理学家级水平。赛后，LYSTO作为轻量级即插即用基准数据集被保留在grand-challenge网站上，并配有自动评估平台。LYSTO已支持肿瘤学中淋巴细胞评估的多项研究。LYSTO将成为深度学习和数字病理学的长期教育挑战，可通过https://lysto.grand-challenge.org/访问。