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Guoyang Xie

m3lab

  •  United Kingdom
  •  University of Surrey
  •  Computer Science
Statistics
  • Member for 2 years

Activity Overview

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TIGER
Challenge User

Grand challenge on automate assessment of tumor infiltrating lymphocytes in digital pathology slides of triple negative and Her2-positive breast cancers

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The PI-CAI Challenge
Challenge User

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI

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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.

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Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022
Challenge User

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Cross-Modality Domain Adaptation: Segmentation & Classification
Challenge User

The CrossMoDA 2022 challenge is the second edition of the first large and multi-class medical dataset for unsupervised cross-modality Domain Adaptation.

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Multi-site, Multi-Domain Airway Tree Modeling (ATM’22)
Challenge User

Airway segmentation is a crucial step for the analysis of pulmonary diseases including asthma, bronchiectasis, and emphysema. The accurate segmentation based on X-Ray computed tomography (CT) enables the quantitative measurements of airway dimensions and wall thickness, which can reveal the abnormality of patients with chronic obstructive pulmonary disease (COPD). Besides, the extraction of patient-specific airway models from CT images is required for navigatiisted surgery.

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MItosis DOmain Generalization Challenge 2022
Challenge User