June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Development of an Automated Segmentation Program to Assess Corneal Suturing Performance of Ophthalmology Residents Using 3D Printed Eye Models
Author Affiliations & Notes
  • Kelly Lauren Mote
    Ophthalmic Biophysics Center, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
  • Yu-Cherng Chang
    Ophthalmic Biophysics Center, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
    Department of Biomedical Engineering, University of Miami College of Engineering, Coral Gables, Florida, United States
  • Florence Cabot
    Ophthalmic Biophysics Center, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
    Anne Bates Leach Eye Hospital, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
  • Karam A Alawa
    Ophthalmic Biophysics Center, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
  • Juan Silgado
    Ophthalmic Biophysics Center, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
  • Cornelis J. Rowaan
    Ophthalmic Biophysics Center, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
  • Madhura Joag
    Anne Bates Leach Eye Hospital, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
  • Sonia H Yoo
    Anne Bates Leach Eye Hospital, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
    Ophthalmic Biophysics Center, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
  • Carol Karp
    Anne Bates Leach Eye Hospital, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
  • Jean-Marie A Parel
    Ophthalmic Biophysics Center, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
    Brien Holden Institute and Vision Cooperative Research Centre, Sydney, New South Wales, Australia
  • Footnotes
    Commercial Relationships   Kelly Mote, None; Yu-Cherng Chang, None; Florence Cabot, None; Karam Alawa, None; Juan Silgado, None; Cornelis Rowaan, None; Madhura Joag, None; Sonia Yoo, None; Carol Karp, None; Jean-Marie Parel, None
  • Footnotes
    Support  The Ronald and Alicia Lepke Grant, The Lee and Claire Hager Grant, The Robert Baer Family Grant The Jimmy and Gaye Bryan Grant, The Richard Azar Family Grant (Institutional grants), The H. Scott Huizenga Grant (CLK), The Florida Lions Eye Bank Research Grant (MJ, CLK). The Florida Lions Eye Bank, Drs. KR Olsen and ME Hildebrandt, Drs. Raksha Urs and Aaron Furtado, The Henri and Flore Lesieur Foundation, Brien Holden Vision Institute (JMP), NIH Center Core Grant P30EY014801 and Research to Prevent Blindness unrestricted grant. Technical support and valuable input were provided by Heather Durkee, Mariela C. Aguilar, Priyanka Chhadva, Basil Williams, BPEI cornea fellows, Aida Grana, Madelin Serpa, Refractive Laser Center, managers and staff of the BPEI operating room.
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 673. doi:
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    • Get Citation

      Kelly Lauren Mote, Yu-Cherng Chang, Florence Cabot, Karam A Alawa, Juan Silgado, Cornelis J. Rowaan, Madhura Joag, Sonia H Yoo, Carol Karp, Jean-Marie A Parel; Development of an Automated Segmentation Program to Assess Corneal Suturing Performance of Ophthalmology Residents Using 3D Printed Eye Models. Invest. Ophthalmol. Vis. Sci. 2017;58(8):673.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : To develop an automated segmentation program to assess corneal suturing performance of ophthalmology residents using 3-D printed eye models and to compare the results with a semi-manual program.

Methods : After cornea suturing, on BIONIKO (Miami, FL) 3D printed eye models, by ophthalmology residents at Bascom Palmer Eye Institute, one eye model was randomly selected to be analyzed using our custom developed segmentation program. A digital camera (Canon EOS 40D DSLR & EF 100mm f/2.8 Macro Lens) was mounted on a microscope stand (AmScope TS130-LED, Irvine, CA) equipped with a centration adaptor holding the 3D printed eye model (Fig 1). Images were taken and imported into MATLAB (Mathworks, Natick, MA) to assess spacing and suture length. Images were preprocessed using an averaging filter and edge detection methods were utilized to isolate sutures and points in the circle of trephination. Spacing was determined by finding the distance between intersection points of the circle of trephination and adjacent sutures. Suture length was determined by the distance between the endpoints of the suture (Fig 2). Results were compared to data obtained with the semi-manual segmentation program previously developed in the laboratory (Alawa K et al, IOVS 2016; 57(12):1224.).

Results : Segmentation of one image took 16.5 seconds with the automated segmentation program and 61.08 seconds with the semi-manual segmentation program. No significant difference was found between the automated and semi-manual programs regarding spacing and suture length. Mean spacing for the 8 sutures was 6.39±0.85 mm using the automated program and 6.33±1.04 mm using the semi-manual program (p=0.92). Mean suture length was 2.53±0.58 mm using the automated program and 2.77±0.47 mm using the semi-manual program (p=0.30).

Conclusions : The automated program was able to calculate the spacing and suture length and yielded results consistent with those obtained with the semi-manual program. Further refinements and calculation of radiality will be needed to optimize the objective assessment of corneal suturing performance provided by this novel automated program.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

 

(A) Side view and (B) front view of the camera mount set up with a 3D printed eye model.

(A) Side view and (B) front view of the camera mount set up with a 3D printed eye model.

 

Original image (A) and a superimposed image (B) of 3D printed eye model with the endpoints and circle of trephination detected from the automated software.

Original image (A) and a superimposed image (B) of 3D printed eye model with the endpoints and circle of trephination detected from the automated software.

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