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Hao Liu

HLiu

  •  China
  •  Shanghai Jiao Tong University
  •  Electronic information
Statistics
  • Member for 3 years, 11 months
  • 41 challenge submissions
  • 23 algorithms run

Activity Overview

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MitoEM
Challenge User

Large-scale 3D mitochondria instance segmentation benchmark

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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.

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Foot Ulcer Segmentation Challenge
Challenge User

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FeTA - Fetal Tissue Annotation Challenge
Challenge User

Fetal Tissue Annotation Challenge

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3D Teeth Scan Segmentation and Labeling Challenge MICCAI2022
Challenge User

Computer-aided design (CAD) tools have become increasingly popular in modern dentistry for highly accurate treatment planning. In particular, in orthodontic CAD systems, advanced intraoral scanners (IOSs) are now widely used as they provide precise digital surface models of the dentition. Such models can dramatically help dentists simulate teeth extraction, move, deletion, and rearrangement and therefore ease the prediction of treatment outcomes. Although IOSs are becoming widespread in clinical dental practice, there are only few contributions on teeth segmentation/labeling available in the literature and no publicly available database. A fundamental issue that appears with IOS data is the ability to reliably segment and identify teeth in scanned observations. Teeth segmentation and labelling is difficult as a result of the inherent similarities between teeth shapes as well as their ambiguous positions on jaws.