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hao Song

Somuns_Y

  •  China
  •  Chongqing University
  •  Chongqing University
Statistics
  • Member for 2 years, 4 months
  • 15 challenge submissions

Activity Overview

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FLARE21
Challenge User

Fast and Low GPU memory Abdominal oRgan sEgmentation Challenge

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KiPA22 (Regular Challenge)
Challenge User

The challenge is aimed to segment kidney, renal tumors, arteries, and veins from computed tomography angiography (CTA) images in one inference.

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Parse2022
Challenge User

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 User

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

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DFUC 2022
Challenge User

Diabetes is a global epidemic affecting around 425 million people and expected to rise to 629 million by 2045. Diabetic Foot Ulcer (DFU) is a severe condition that can result from the disease. The rise of the condition over the last decades is a challenge for healthcare systems. Cases of DFU usually lead to severe conditions that greatly prolongs treatment and result in limb amputation or death. Recent research focuses on creating detection algorithms to monitor their condition to improve patient care and reduce strain on healthcare systems. Work between Manchester Metropolitan University, Lancashire Teaching Hospitals and Manchester University NHS Foundation Trust has created an international repository of up to 11,000 DFU images. Analysis of ulcer regions is a key for DFU management. Delineation of ulcers is time-consuming. With effort from the lead scientists of the UK, US, India and New Zealand, this challenge promotes novel work in DFU segmentation and promote interdisciplinary researcher collaboration.