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Tang Wenqi

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  •  China
  •  Beijing University of Posts and Telecommunications
  •  School of Artificial Intelligence
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  • Member for 4 years, 8 months
  • 1 challenge submissions

Activity Overview

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LOLA11
Challenge User

The goal of LOLA11 (LObe and Lung Analysis 2011) is to compare methods for (semi-)automatic segmentation of the lungs and lobes from chest computed tomography scans. Any team, whether from academia or industry, can join.

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DRIVE
Challenge User

Develop a system to automatically segment vessels in human retina fundus images.

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CHAOS
Challenge User

In this challenge, you segment the liver in CT data, and segment liver, spleen, and kidneys in MRI data.

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PAIP2020
Challenge User

Built on the success of its predecessor, PAIP2020 is the second challenge organized by the Pathology AI Platform (PAIP) and the Seoul National University Hospital (SNUH). PAIP2020 will proceed to not only detect whole tumor areas in colorectal cancers but also to classify their molecular subtypes, which will lead to characterization of their heterogeneity with respect to prognoses and therapeutic responses. All participants should predict one of the molecular carcinogenesis pathways, i.e., microsatellite instability(MSI) in colorectal cancer, by performing digital image analysis without clinical tests. This task has a high clinical relevance as the currently used procedure requires an extensive microscopic assessment by pathologists. Therefore, those automated algorithms would reduce the workload of pathologists as a diagnostic assistance.

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Cross-Modality Domain Adaptation Image Segmentation - 2021
Challenge User

The CrossMoDA challenge 2021 introduces the first large and multi-class medical dataset for unsupervised cross-modality Domain Adaptation.

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BCNB
Challenge Editor

Early Breast Cancer Core-Needle Biopsy WSI Dataset