Real-Time Multimodal Retinal Image Registration for a Computer Assisted Laser Photocoagulation System

Broehan, A; Rudolph, T; Amstutz, C; Kowal, J (2011). Real-Time Multimodal Retinal Image Registration for a Computer Assisted Laser Photocoagulation System. IEEE transactions on biomedical engineering, 58(10), pp. 2816-24. New York, N.Y.: Institute of Electrical and Electronics Engineers IEEE 10.1109/TBME.2011.2159860

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An algorithm for the real-time registration of a retinal video sequence captured with a scanning digital ophthalmoscope (SDO) to a retinal composite image is presented. This method is designed for a computer-assisted retinal laser photocoagulation system to compensate for retinal motion and hence enhance the accuracy, speed, and patient safety of retinal laser treatments. The procedure combines intensity and feature-based registration techniques. For the registration of an individual frame, the translational frame-to-frame motion between preceding and current frame is detected by normalized cross correlation. Next, vessel points on the current video frame are identified and an initial transformation estimate is constructed from the calculated translation vector and the quadratic registration matrix of the previous frame. The vessel points are then iteratively matched to the segmented vessel centerline of the composite image to refine the initial transformation and register the video frame to the composite image. Criteria for image quality and algorithm convergence are introduced, which assess the exclusion of single frames from the registration process and enable a loss of tracking signal if necessary. The algorithm was successfully applied to ten different video sequences recorded from patients. It revealed an average accuracy of 2.47 ± 2.0 pixels (∼23.2 ± 18.8 μm) for 2764 evaluated video frames and demonstrated that it meets the clinical requirements.

Item Type:

Journal Article (Original Article)


10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Medical Imaging Laboratory
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Ophthalmology

UniBE Contributor:

Rudolph, Tobias, Amstutz, Christoph Andreas, Kowal, Horst Jens




Institute of Electrical and Electronics Engineers IEEE




Factscience Import

Date Deposited:

04 Oct 2013 14:12

Last Modified:

05 Dec 2022 14:02

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URI: (FactScience: 205509)

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