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caiyi chen

ccy754504392

  •  China
  •  FJNU
  •  School of Computer and Cyberspace Security
Statistics
  • Member for 5 months, 1 week
  • 3 challenge submissions

Activity Overview

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DRIVE
Challenge User

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

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CHAIMELEON Open Challenges
Challenge User

A unique opportunity for scientists to advance cancer research with AI. The CHAIMELEON Open Challenges invites participants to collaborate to develop and train new AI-powered solutions driving innovation in cancer diagnosis and treatment.

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Universal Lesion Segmentation Challenge '23
Challenge User

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Justified Referral in AI Glaucoma Screening
Challenge User

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Light My Cells : Bright Field to Fluorescence Imaging Challenge
Challenge User

Join the Light My Cells France-Bioimaging challenge! Enhance biology and microscopy by contributing to the development of new image-to-image deep labelling methods. The task: predict the best-focused output images of several fluorescently labelled organelles from label-free transmitted light input images. Dive into the future of imaging with us! 🌐🔬 #LightMyCellsChallenge

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Diminished Reality for Emerging Applications in Medicine
Challenge User

The Diminished Reality for Emerging Applications in Medicine through Inpainting (DREAMING) challenge seeks to pioneer the integration of Diminished Reality (DR) into oral and maxillofacial surgery. While Augmented Reality (AR) has been extensively explored in medicine, DR remains largely uncharted territory. DR involves virtually removing real objects from the environment by replacing them with their background. Recent inpainting methods present an opportunity for real-time DR applications without scene knowledge. DREAMING focuses on implementing such methods to fill obscured regions in surgery scenes with realistic backgrounds, emphasizing the complex facial anatomy and patient diversity. The challenge provides a dataset of synthetic yet photorealistic surgery scenes featuring humans, simulating an operating room setting. Participants are tasked with developing algorithms that seamlessly remove disruptions caused by medical instruments and hands, offering surgeons an unimpeded view of the operative site.

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Pelvic Bone Fragments with Injuries Segmentation Challenge
Challenge User

Pelvic fracture segmentation in CT and X-ray