FGAI4H-H-017-A03 Brasilia, 22-24 January 2020 - PowerPoint Presentation

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FGAI4H-H-017-A03

Brasilia, 22-24 January 2020

Source:TG-Ophthalmo topic driverTitle:TDD update: TG-Ophthalmo (Ophthalmology)Purpose:Discussion

Contact:Arun ShroffE-mail: arun@xtend.ai

Abstract:

This PPT summarizes the content of

H-017-A01

with the TDD for the

TG on ophthalmology

, for presentation and discussion during the meeting.

Meeting G Topic Group UpdateOphthalmology (TG-Ophthalmo

)Brasilia, Jan 20 – 24, 2020Arun Shroff,

Topic Driver, TG-Ophthalmology

Topic Group – Ophthalmology

Sub-topics in this group:

Diabetic Retinopathy (DR) Age Related Macular Degeneration (AMD)Glaucoma (GC) Pathological Myopia (PM)Red Eye (RE) – (Added Meeting G)Topic Group Description Document (FGAI4H-H-017-A01) Topic Group Call for Participation (FGAI4H-H-017-A02) Topic Group Collaboration Site: https://extranet.itu.int/sites/itu-t/focusgroups/ai4h/tg/SitePages/TG-Ophthalmo.aspx

The Health Challenge

Diabetic Retinopathy (DR)

At risk population - 422M people with diabetes worldwide (2014)35%, 148M have DR / 11%, 48M have Vision Threatening DR (64M by 2040) Leading cause of blindness among adults worldwideAge Related Macular Degeneration (AMD) Damages macula and impairs central vision 196M by 2020Third leading cause of vision loss overall, leading cause for those over 50

The Health Challenge

Glaucoma (GC)

Damages optic nerve & leads to vision loss 80M by 2020Pathological Myopia (PM) Global Prevalence is 0.9% to 3.1%35% of people with myopia have High Myopia, which can develop into PMRed Eye [Added Meeting G] 2-3% visits to primary health centers & emergency facilities due to eye problems & majority are due to Red Eye. May denote more serious conditions like keratitis, iritis, glaucoma, which could lead to vision loss

Impact of AI

Bridge acute shortage of healthcare professionals in LMICs, rural areas.

Provide earlier detection and prevent vision loss for millions. Decrease healthcare costs via earlier interventions Increase overall efficiency and scalability of current screening methods.

Benchmarking: DR Classifications

Binary:

[0 (Nogradable Image)] (Optional) 1 (Non-referable Retinopathy = Normal or Mild) 2 (Referable Retinopathy = Moderate, Severe, PDR) Multi-class Classification: [0 (Nongradable Image) ] (Optional) 1(Normal) 2 (Mild) 3 (Moderate NPDR) 4 (Severe NPDR) 5 (PDR)

Benchmarking: AMD, GC, PM Classifications

AMD:

[0 (Image Nongradable)]1 (No/early stage AMD 2 (Intermediate/advanced stage AMD) GC: [0 (Image Nongradable.]1 (No GC)2 (GC)Optic Disk PM: [0 (Image Nongradable)]1 (No PM/HM)2 (HM: high myopia)3 (PM)

Available Datasets - DR

EyePACS

dataset: Approx 90,000 fundus images, 5 levels of severity Kaggle: (derived from EyePACS)Approx 35,000 images : 5 levels of severity Aptos 2019 Challenge : 3664 images : 5 levels of severity

MESSIDOR dataset: 1,200 images, 4 levels of severity DiaRetDB dataset: ~ 200 images marked with lesions etc

Available Datasets - AMD, GC

AMD:

AREDS dataset: (Age Related Eye Disease Study )Images from ~4700 patients : KORA dataset: (Cooperative Health Research in the Region of Augsburg (KORA) dataset,)Approx 2840 patient records

GC: ORIGA, 650 fundus imagesRetinal fundus images for glaucoma analysis (RIGA, 760 images) ACHIKO-K (258 images)DRISHTI-GS (100 images)

Benchmarking Metrics

Sensitivity:

% of positive (disease) cases correctly classified True Positive/(True Positive + False Negative)Specificity: % of negative (normal) cases correctly classified True Negative/(True Negative + False Positive)AUC (Area Under ROC);Sensitivity Vs (1-Specificity) plotted at different points of the model

Precision/Accuracy, F1 Score Cohen’s Kappa / Quadratic Kappa Score:

Topic Group History

Meeting B - New York, 15-16 November 2018AI for Ophthalmology Use Case submitted in response to the Call for Proposals

“Using AI for Early Detection of DR to Prevent Vision Loss” accepted as a use caseMeeting C - Lausanne, Switzerland, 22-25 January 2019Status report on the use case “Using AI for Early Detection of DR”Topic Group “Ophthalmology” established 2 Members : Medindia.net / Xtend.ai Baidu, China.

Topic Group History

Meeting D- Shanghai, April 2-5, 2019First version of Topic Description Document (TDD) – Version 1.0 completed Topic Group Status Update provided.

Meeting E - Geneva, May 30 – June 1, 2019Topic Description Document (TDD) Updated Pathological Myopia (PM) added (by Xingxing Cao, Baidu) Reviewed and validated by topic group membersNew topic group members: Ashley Kras, M.D. M. S., Ophthalmologist & Bioinformatician

Topic Group History

Meeting F - Zanzibar, Sep 2-5, 2019Topic Description Document (TDD) - FGAI4H-F-012 Updated and edits / Corrections made

New Topic group members:Dr Covadonga Bascaran, PHEC MSc Programme Director, International Centre for Eye Health (ICEH), London School of Hygiene & Tropical Medicine Inês Sousa , Head of Intelligent Systems, Fraunhofer PortugalNew TG submission: DR-NET (Diabetic Retinopathy Network) - FGAI4H-F-020A network of DR screening programmes in LMICs (29 countries)Contribution of data from different countries to make data representativePossibility of getting undisclosed data sets for testingImages are not currently annotated/labeled – this would need to be done

Meeting G (New Delhi, Nov 11-15, 2019:

Online Meeting - Nov 7, 2019 - 16:00 – 17:00 CET.Attendees: Parvathi Ram (India), Rami

Verbin (Israel), Arun Shroff (USA)Topics Discussed : TDD status and updatesNew TG Submission (Red Eye detection) New collaboration features for TGDatasetsTopic Group History

Progress since Meeting G:

New dedicated mailing list for topic group - fgai4htgophthalmo@lists.itu.int​​​ (17 members)

Email to topic group members, online meeting scheduled. No new inputs or contributionsTDD Updated to incorporate submissions received during Meeting G: FGAI4H-G-030-R01 (St, John’s Medical College) on Red Eye incorporated into relevant sections. FG-AI4H-G-028 (Calligo Technologies) on Leveraging Edge Analytics incorporated into current AI systems overview.  Other TDD updates:Topic Group Thematic Classification updated. Added Quadratic Kappa Metric for multi-label classification. Added Kaggle DR challenge datasets and resultsMiscellaneous edits/correctionsTopic Group History

Topic Group – Ophthalmology Members

Arun Shroff,

Xtend.AI and Medindia.net, Topic Driver for TG-OphthalmologyYanwu XU, Artificial Intelligence Innovation Business, Chief Scientist, Baidu, ChinaXingxing Cao, Artificial Intelligence Group, Baidu, China Jingyu WANG, Artificial Intelligence Group, Baidu, China Shan Xu, CAICT, China Ashley Kras, M.D. M. S., Ophthalmologist & Bioinformatician (Harvard Medical School)Covadonga Bascaran, PHEC MSc Programme Director, International Centre for Eye Health (ICEH), London School of Hygiene & Tropical Medicine, U.K. Inês Sousa, Head of Intelligent Systems, Fraunhofer Portugal AICOS

Parvathi Ram, St. John’s Medical College, IndiaDr Suneetha N, St John’s Medical College, IndiaDr. Sheila John, Sankara Netralaya, Chennai, IndiaRajaraman Subramanian, Calligo Technologies, India Sriganesh Rao, Calligo Technologies, India Sushil Kumar TEC, New Delhi India

Next Steps

Topic Description Document Complete missing sections of TDD Ethical considerationsUndisclosed test data set collection

Benchmarking methodology and architectureReporting methodology Dataset Procurement: Follow-up with DR-Net, EyePACs, Moorefields, Open Eye, Aravind Eye Hospital for undisclosed datasets for testing Outreach / Community BuildingIncrease engagement from membersGet more experts on board and involved.

Thank you!