Aim

The goal of the challenge is to evaluate new and existing algorithms for liver cancer segmentation in whole-slide images (WSIs).

Background

The liver is a visceral organ most often involved in the metastatic spread of cancer. For the best practice, early diagnosis of liver cancer is important but many people don’t even know that they have hepatitis. Hepatocellular Carcinoma(HCC) represents about 90% of primary liver cancers and constitutes a major global health problem. The incidence of HCC is increasing both in Korea and worldwide; it is amongst the leading causes of cancer mortality globally. Between 1990 and 2015 newly diagnosed HCC cases increased by 75%, mainly due to changing age structures and population growth.

A tumor is composed of various cellular and stromal components, eg tumor cells, inflammatory cells, blood vessels, acellular matrix, tumor capsule, fluid, mucin, or necrosis. The viable tumor burden is defined as the ratio of viable tumor area to the whole area of the tumor. The need for evaluation of viable tumor burden is increasing, as an assessment of response rates for chemoradiotherapy or proportion of tumor cells in genetic testing using tissue samples. Traditional pathologists use a semiquantitative grading system for residual tumor burden or report portion of necrosis indirectly indicating viable tumor burden.

Results

Challenge

https://paip2019.grand-challenge.org