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Winnie Zhang

winniezhangcoding

  •  Hong Kong
  •  The University of Hong Kong
  •  Computer Science
Statistics
  • Member for 2 years, 5 months
  • 28 challenge submissions
  • 10 algorithms run

Activity Overview

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PAIP 2019
Challenge User

PAIP2019: Liver Cancer Segmentation Task 1: Liver Cancer Segmentation Task 2: Viable Tumor Burden Estimation

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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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CoNIC 2022
Challenge User

Colon Nuclei Identification and Counting Challenge 2022

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Cell Segmentation in Multi-modality Microscopy Images
Challenge User

Weakly Supervised Cell Segmentation in Multi-modality High-resolution Microscopy Images