research-article

Cataract-101: video dataset of 101 cataract surgeries

Authors:

Manfred Jürgen Primus,

Doris PutzgruberAuthors Info & Claims

MMSys '18: Proceedings of the 9th ACM Multimedia Systems Conference

Pages 421 - 425

https://doi.org/10.1145/3204949.3208137

Published: 12 June 2018 Publication History

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Abstract

Cataract surgery is one of the most frequently performed microscopic surgeries in the field of ophthalmology. The goal behind this kind of surgery is to replace the human eye lense with an artificial one, an intervention that is often required due to aging. The entire surgery is performed under microscopy, but co-mounted cameras allow to record and archive the procedure. Currently, the recorded videos are used in a postoperative manner for documentation and training. An additional benefit of recording cataract videos is that they enable video analytics (i.e., manual and/or automatic video content analysis) to investigate medically relevant research questions (e.g., the cause of complications). This, however, necessitates a medical multimedia information system trained and evaluated on existing data, which is currently not publicly available. In this work we provide a public video dataset of 101 cataract surgeries that were performed by four different surgeons over a period of 9 months. These surgeons are grouped into moderately experienced and highly experienced surgeons (assistant vs. senior physicians), providing the basis for experience-based video analytics. All videos have been annotated with quasi-standardized operation phases by a senior ophthalmic surgeon.

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Cited By

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Tu PYe HShi HYoung JXie MZhao PZheng CJiang XChen X(2025)Phase-specific augmented reality guidance for microscopic cataract surgery using spatiotemporal fusion networkInformation Fusion10.1016/j.inffus.2024.102604113(102604)Online publication date: Jan-2025
https://doi.org/10.1016/j.inffus.2024.102604
Müller SJain MSachdeva BShah PHolz FFinger RMurali KWintergerst MSchultz T(2024)Artificial Intelligence in Cataract Surgery: A Systematic ReviewTranslational Vision Science & Technology10.1167/tvst.13.4.2013:4(20)Online publication date: 15-Apr-2024
https://doi.org/10.1167/tvst.13.4.20
Yang YWang HWang JDong KDing S(2024)Semantic-Preserving Surgical Video Retrieval With Phase and Behavior Coordinated HashingIEEE Transactions on Medical Imaging10.1109/TMI.2023.332138243:2(807-819)Online publication date: Feb-2024
https://doi.org/10.1109/TMI.2023.3321382
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Index Terms

Cataract-101: video dataset of 101 cataract surgeries
1. Applied computing
  1. Life and medical sciences
    1. Health informatics
2. Information systems
  1. Information retrieval
    1. Evaluation of retrieval results
      1. Test collections

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Published In

MMSys '18: Proceedings of the 9th ACM Multimedia Systems Conference

June 2018

604 pages

ISBN:9781450351928

DOI:10.1145/3204949

General Chair:
Pablo Cesar
Centrum Wiskunde & Informatica, The Netherlands
,
Program Chairs:
Michael Zink
University of Massachusetts Amherst
,
Niall Murray
Athlone Institute of Technology, Ireland

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 June 2018

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Funding Sources

Carinthian Economic Promotion Fund (KWF)
European Regional Development Fund

Conference

MMSys '18

Sponsor:

SIGMM

MMSys '18: 9th ACM Multimedia Systems Conference

June 12 - 15, 2018

Amsterdam, Netherlands

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Overall Acceptance Rate 176 of 530 submissions, 33%

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Tu PYe HShi HYoung JXie MZhao PZheng CJiang XChen X(2025)Phase-specific augmented reality guidance for microscopic cataract surgery using spatiotemporal fusion networkInformation Fusion10.1016/j.inffus.2024.102604113(102604)Online publication date: Jan-2025
https://doi.org/10.1016/j.inffus.2024.102604
Müller SJain MSachdeva BShah PHolz FFinger RMurali KWintergerst MSchultz T(2024)Artificial Intelligence in Cataract Surgery: A Systematic ReviewTranslational Vision Science & Technology10.1167/tvst.13.4.2013:4(20)Online publication date: 15-Apr-2024
https://doi.org/10.1167/tvst.13.4.20
Yang YWang HWang JDong KDing S(2024)Semantic-Preserving Surgical Video Retrieval With Phase and Behavior Coordinated HashingIEEE Transactions on Medical Imaging10.1109/TMI.2023.332138243:2(807-819)Online publication date: Feb-2024
https://doi.org/10.1109/TMI.2023.3321382
Wang SWang SYang DLi MKuang HZhao XSu LZhai PZhang L(2024)CPR-Coach: Recognizing Composite Error Actions Based on Single-Class Training2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01777(18782-18792)Online publication date: 16-Jun-2024
https://doi.org/10.1109/CVPR52733.2024.01777
Zhang YZheng PYan WFang CCheng S(2024)A Unified Framework for Microscopy Defocus Deblur with Multi-Pyramid Transformer and Contrastive Learning2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01058(11125-11136)Online publication date: 16-Jun-2024
https://doi.org/10.1109/CVPR52733.2024.01058
Schmidgall SKim JKuntz AGhazi AKrieger A(2024)General-purpose foundation models for increased autonomy in robot-assisted surgeryNature Machine Intelligence10.1038/s42256-024-00917-4Online publication date: 1-Nov-2024
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Balu AKugener GPangal DLee HLasky SHan JBuchanan ILiu JZada GDonoho D(2024)Simulated outcomes for durotomy repair in minimally invasive spine surgeryScientific Data10.1038/s41597-023-02744-511:1Online publication date: 10-Jan-2024
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Matta SLamard MZhang PLe Guilcher ABorderie LCochener BQuellec G(2024)A systematic review of generalization research in medical image classificationComputers in Biology and Medicine10.1016/j.compbiomed.2024.109256183(109256)Online publication date: Dec-2024
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Zhang BSarhan MGoel BPetculescu SGhanem A(2024)SF-TMN: SlowFast temporal modeling network for surgical phase recognitionInternational Journal of Computer Assisted Radiology and Surgery10.1007/s11548-024-03095-119:5(871-880)Online publication date: 21-Mar-2024
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Li YZhao ZLi RLi F(2024)Deep learning for surgical workflow analysis: a survey of progresses, limitations, and trendsArtificial Intelligence Review10.1007/s10462-024-10929-657:11Online publication date: 16-Sep-2024
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