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chaonan feng

FengCN

  •  China
  •  shenzhen university
  •  student
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  • Member for 1 year, 1 month

Activity Overview

LUNA16 Logo
LUNA16
Challenge User

The LUNA16 challenge: automatic nodule detection on chest CT

SLIVER07 Logo
SLIVER07
Challenge User

The goal of this competition is to compare different algorithms to segment the liver from clinical 3D computed tomography (CT) scans.

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ROCC
Challenge User

Retinal OCT Classification Challenge (ROCC) is organized as a one day Challenge in conjunction with MVIP2017. The goal of this challenge is to call different automated algorithms that are able to detect DR disease from normal retina on a common dataset of OCT volumes, acquired with Topcon SD-OCT devices.

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DRIVE
Challenge User

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

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ODIR-2019
Challenge User

北京大学国际眼底图像智能识别竞赛 Peking University International Competition on Ocular Disease Intelligent Recognition

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LNDb Challenge
Challenge User

Lung cancer screening and Fleischner follow-up determination in chest CT through nodule detection, segmentation and characterization

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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.

Carotid Artery Vessel Wall Segmentation Challenge
Challenge User

To segment the vessel wall of the carotid artery on black-blood MRI images

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The PI-CAI Challenge
Challenge User

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI

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ATLAS R2.0 - Stroke Lesion Segmentation
Challenge User

Anatomical Tracings of Lesions After Stroke

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SynthRAD2023
Challenge User

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

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Shifts Challenge 2022
Challenge User

The goal of the Shifts Challenge 2022 is to raise awareness among the research community about the problems of distributional shift, robustness, and uncertainty estimation, and to identify new solutions to address them. The competition will consist of two new tracks: White Matter Multiple Sclerosis (MS) lesion segmentation in 3D Magnetic Resonance Imaging (MRI) of the brain and Marine cargo vessel power estimation.

isles22 Logo
Ischemic Stroke Lesion Segmentation Challenge
Challenge User

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

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

HaN-Seg2023 Logo
The Head and Neck Organ-at-Risk CT & MR Segmentation Challenge
Challenge User

A semantic multimodal segmentation challenge comprising 30 organs at risk

SegRap2023 Logo
SegRap 2023
Challenge User

A segmentation challenge with 200 patients (two modalities of CT images, 45 OARs and 2 GTVs).

BONBID-HIE2023 Logo
Hypoxic Ischemic Encephalopathy Lesion Segmentation Challenge
Challenge User

ISLES-24 Logo
Ischemic Stroke Lesion Segmentation Challenge 2024
Challenge User

BONBID-HIE2024 Logo
2nd BONBID-HIE Challenge for HIE Outcome Prediction and Lesion S
Challenge User