Welcome to the "Retinal Image Analysis for multi-Disease Detection Challenge" website. This challenge was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI-2021), Nice Acropolis Convention, and Exhibition Centre, France. On April 13th, 2021 we organized the workshop on "Retinal Image Analysis for multi-Disease Detection" during ISBI-2021. More information about the workshop can be found here.


 Aim

The aim of this challenge is to evaluate algorithms for the automated classification of different ocular diseases using retinal fundus images.


Abstract

According to the WHO,  World report on vision 2019, the number of visually impaired people worldwide is estimated to be 2.2 billion, of whom at least 1 billion have a vision impairment that could have been prevented or is yet to be addressed. The world faces considerable challenges in terms of eye care, including inequalities in the coverage and quality of prevention, treatment, and rehabilitation services. Early detection and diagnosis of ocular pathologies would enable forestall of visual impairment. One challenge that limits the adoption of a computer-aided diagnosis tool by the ophthalmologist is, the sight-threatening rare pathologies such as central retinal artery occlusion or anterior ischemic optic neuropathy and others are usually ignored. In the past two decades, many publicly available datasets of color fundus images have been collected with a primary focus on diabetic retinopathy, glaucoma, and age-related macular degeneration, and few other frequent pathologies. The aim of this challenge is to unite the medical image analysis community to develop methods for automatic ocular disease classification of frequent diseases along with the rare pathologies. For this purpose, we have created a new Retinal Fundus Multi-disease Image Dataset (RFMiD) consisting of a total of 3200 fundus images captured using three different fundus cameras with 46 conditions annotated through adjudicated consensus of two senior retinal experts. To the best of our knowledge, our dataset, RFMiD is the only publicly available dataset that constitutes such a wide variety of diseases that appear in routine clinical settings. This challenge will enable the development of generalizable models for screening retina, unlike the previous efforts that focused on the detection of specific diseases.


This challenge is divided into two sub-tasks:
  • Disease Screening (For more details please refer to Sub-challenge-1)
  • Disease/pathology Classification (For more details please refer to Sub-challenge-2)

Important Dates
  • 01 Nov 2020: Challenge Website Launch
  • 08 Nov 2020: Registration open
  • 22 Nov 2020: Training Data Release (Images + Ground truth)
  • 29 Nov 2020: Off-site Evaluation (only Images) Data Release.
  • 01 Dec 2020: Submissions open for evaluation of results (on the off-site evaluation set).
  • 28 Feb 2021: Off-site validation set results submission deadline.
  • 5 Mar 2021: Paper submission deadline (Microsoft CMT paper submission system).
  • 15 Mar 2021: Tentative Off-site leaderboard update and call for participation to top-performing teams (subjected to ISBI registration)
  • 18 Mar 2021: ISBI registration deadline
  • 20 Mar 2021: Final Off-site leaderboard update and the display of top teams upon participation confirmation.
  • 13 April 2021: On-site challenge at ISBI 2021.

Related Work:
  • Gwenol√© Quellec, Mathieu Lamard, Pierre-Henri Conze, Pascale Massin, and B√©atrice Cochener. "Automatic detection of rare pathologies in fundus photographs using few-shot learning." Medical Image Analysis 61 (2020): 101660.

Prize Sponsor:
 

Details will be updated soon.

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