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Song Tian

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  •  China
  •  Null
  •  Null
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  • Member for 2 years, 7 months

Activity Overview

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KiTS19
Challenge Participant

2019 Kidney and Kidney Tumor Segmentation Challenge

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COVID-19 LUNG CT LESION SEGMENTATION CHALLENGE - 2020
Challenge Participant

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 Participant

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

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Cross-Modality Domain Adaptation Image Segmentation - 2021
Challenge Participant

The CrossMoDA challenge 2021 introduces the first large and multi-class medical dataset for unsupervised cross-modality Domain Adaptation.

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fastPET-LD
Challenge Participant

The purpose of this challenge is the detection of “hot spots” in fast PET scan, that is locations that have an elevated standard uptake value (SUV) and potential clinical significance. Corresponding CT scans are also provided. The ground truth, common to both datasets, was generated by a nuclear medicine expert. It consists of a 3-D segmentation map of the hot spots as well as a text file containing the position and size of 3D cuboid bounding box for each hot spot.

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STOIC2021 - COVID-19 AI Challenge
Challenge Participant

COVID-19 Artificial Intelligence Challenge: automated diagnosis, and prognostic evaluation based on computed tomography

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AIROGS
Challenge Participant

Artificial Intelligence for RObust Glaucoma Screening Challenge

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Parse2022
Challenge Participant

It is of significant clinical interest to study pulmonary artery structures in the field of medical image analysis. One prerequisite step is to segment pulmonary artery structures from CT with high accuracy and low time-consuming. The segmentation of pulmonary artery structures benefits the quantification of its morphological changes for diagnosis of pulmonary hypertension and thoracic surgery. However, due to the complexity of pulmonary artery topology, automated segmentation of pulmonary artery topology is a challenging task. Besides, the open accessible large-scale CT data with well labeled pulmonary artery are scarce (The large variations of the topological structures from different patients make the annotation an extremely challenging process). The lack of well labeled pulmonary artery hinders the development of automatic pulmonary artery segmentation algorithm. Hence, we try to host the first Pulmonary ARtery SEgmentation challenge in MICCAI 2022 (Named Parse2022) to start a new research topic.

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INSTANCE2022
Challenge Participant

The 2022 Intracranial Hemorrhage Segmentation Challenge on Non-Contrast head CT (NCCT)

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MICCAI FLARE 2022
Challenge Participant

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

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K2S: from undersampled K-space To automatic Segmentation
Challenge Participant

K2S: from undersampled K-space To automatic Segmentation

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Low-dose Computed Tomography Perceptual Image Quality Assessment
Challenge Participant

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