Cataract Surgery

Aims: Develop technology to enable an automated co-pilot for eye surgeons.

Summary: This project aims to develop technology to enable a system that can function as an automated co-pilot for surgeons using cataract surgery as a testbed procedure. Given video of the surgical field during a procedure, this system segments the procedure into constituent activities, assign a skill rating for each activity, and provide commensurate feedback to the surgeon. This project relies upon multiple modes of data including video images and verbal and textual surgical narratives.

Funding: The Wilmer Eye Institute Pooled Professors Fund 2016 (PI: Dr. Shameema Sikder), and an unrestricted research grant to The Wilmer Eye from Research to Prevent Blindness

People: Shameema Sikder, S. Swaroop Vedula, Gregory D. Hager, Anand Malpani, Sidra Zafar, Tae Soo Kim


  1. Kim TS, O’Brien M, Zafar S, Hager GD, Sikder S, Vedula SS. Objective assessment of intraoperative technical skill in capsulorhexis using videos of cataract surgery. Int J CARS [Internet]. 2019 Apr 11 [cited 2019 Apr 19]; Available from:
  2. Yu F, Silva Croso G, Kim TS, Song Z, Parker F, Hager GD, Reiter A, Vedula SS, Ali H, Sikder S. Assessment of Automated Identification of Phases in Videos of Cataract Surgery Using Machine Learning and Deep Learning Techniques. JAMA Netw Open [Internet]. 2019 Apr 5 [cited 2019 Dec 17];2(4). Available from: PMCID: PMC6450320
  3. Kim TS, Malpani A, Reiter A, Hager GD, Sikder S, Swaroop Vedula S. Crowdsourcing Annotation of Surgical Instruments in Videos of Cataract Surgery. In: Stoyanov D, Taylor Z, Balocco S, Sznitman R, Martel A, Maier-Hein L, Duong L, Zahnd G, Demirci S, Albarqouni S, Lee S-L, Moriconi S, Cheplygina V, Mateus D, Trucco E, Granger E, Jannin P, editors. Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis. Granada, Spain: Springer International Publishing; 2018. p. 121–130.