- Grand Challenge

Kaifeng Song

kaifengsong0

China
Beijing Institute Of Technology
School of Information and Electronics Beijing Institute of Technology

Statistics

Member for 3 years, 8 months

Activity Overview

QUBIQ

Challenge User

Quantification of Uncertainties in Biomedical Image Segmentation Challenge

COVID-19 LUNG CT LESION SEGMENTATION CHALLENGE - 2020

Challenge User

This challenge will create the platform to evaluate emerging methods for the segmentation and quantification of lung lesions caused by SARS-CoV-2 infection from CT images.

Where is VALDO?

Challenge User

Vascular Lesion Detection Challenge at MICCAI 2021

EndoCV2021

Challenge User

Endoscopy Computer Vision Challenge 2021

NuCLS

Challenge User

Classification, Localization and Segmentation of nuclei in scanned FFPE H&E stained slides of triple-negative breast cancer from The Cancer Genome Atlas. See: Amgad et al. 2021. arXiv:2102.09099 [cs.CV].

Breast Cancer Segmentation

Challenge User

Semantic segmentation of histologic regions in scanned FFPE H&E stained slides of triple-negative breast cancer from The Cancer Genome Atlas. See: Amgad M, Elfandy H, ..., Gutman DA, Cooper LAD. Structured crowdsourcing enables convolutional segmentation of histology images. Bioinformatics. 2019. doi: 10.1093/bioinformatics/btz083

WSSS4LUAD

Challenge User

The WSSS4LUAD dataset contains over 10,000 patches of lung adenocarcinoma from whole slide images from Guangdong Provincial People's Hospital and TCGA with image-level annotations. The goal of this challenge is to perform semantic segmentation for differentiating three important types of tissues in the WSIs of lung adenocarcinoma, including cancerous epithelial region, cancerous stroma region and normal region. Paticipants have to use image-level annotations to give pixel-level prediction.