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Elliot Qi

elliotqii

  •  China
  •  CSU
  •  Computer Science and Engineering
Statistics
  • Member for 2 years, 8 months
  • 34 challenge submissions
  • 3 algorithms run

Activity Overview

MELA Logo
MELA2022
Challenge User

MICCAI 2022 MELA Challenge: A Large-Scale Detection Benchmark of 1,100 CT Scans for Mediastinal Lesion Analysis

SynthRAD2023 Logo
SynthRAD2023
Challenge User

SynthRAD is the first challenge on automatic generation of synthetic computed tomography (sCT) for radiotherapy

3DTeethSeg Logo
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.

FLARE22 Logo
MICCAI FLARE 2022
Challenge User

MICCAI 2022 Fast and Low-resource semi-supervised Abdominal oRgan sEgmentation (FLARE) Challenge

AMOS22 Logo
Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022
Challenge User

SurgToolLoc Logo
Surgical Tool Localization in endoscopic videos
Challenge User

curious2022 Logo
Brain shift with Intraoperative Ultrasound - Segmentation tasks
Challenge User

ATM22 Logo
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.

NeurIPS22-CellSeg Logo
Cell Segmentation in Multi-modality Microscopy Images
Challenge User

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

UltrasoundEnhance2023 Logo
Ultrasound Image Enhancement challenge 2023
Challenge User

LDCTIQAC2023 Logo
Low-dose Computed Tomography Perceptual Image Quality Assessment
Challenge User