Computer-aided retinal photocoagulation system

Optimal scheduling of tracing computations for real-time vascular landmark extraction from retinal fundus images

Recently, this group published fast algorithms for automatic tracing (vectorization) of the vasculature in live retinal angiograms, and for the extraction of visual landmarks formed by vascular bifurcations and crossings. These landmarks are used for feature-based image matching for controlling a computer-assisted laser retinal surgery instrument currently under development. This paper describes methods to schedule the vascular tracing computations to maximize the rate of growth of quality of the partial tracing results within a frame cycle. There are two main advantages. First, progressive image matching from partially extracted landmark sets can be faster, and provide an earlier indication of matching failure. Second, the likelihood of successful image matching is greatly improved since the extracted landmarks are of the highest quality for the given computational budget. The scheduling method is based on quantitative measures for the computational work and the quality of landmarks. A coarse grid-based analysis of the image is used to generate seed points for the tracing computations, along with estimates of local edge strengths, orientations, and vessel thickness. These estimates are used to define criteria for real-time preemptive scheduling of the tracing computations. It is shown that the optimal schedule can only be achieved in perfect hindsight, and is thus unrealizable. This leads to scheduling heuristics that approximate the behavior of the optimal algorithm. One such approximation produced approximately 400% improvement in the quality of the partial results at a defined milestone, as compared to random scheduling. The resulting algorithm can be readily implemented on conventional and multiple-processor systems, and is being applied to computer-assisted laser retinal surgery.

Initial in vivo results of a hybrid retinal photocoagulation system

We describe initial in vivo experimental results of a new hybrid digital and analog design for retinal tracking and laser beam control. An overview of the design is given. The results show in vivo tracking rates which exceed the equivalent of 38 degrees/s in the eye. A robotically assisted lesion pattern is created for laser surgery to treat conditions such as diabetic retinopathy and retinal breaks.

Computer-vision-enabled augmented reality fundus biomicroscopy

PURPOSE

To guide treatment for macular diseases and to facilitate real-time image measurement and comparison, investigations were initiated to permit overlay of previously stored photographic and angiographic images directly onto the real-time slit-lamp biomicroscopic fundus image.

DESIGN

Experimental study in model eyes, and preliminary observations in human subjects.

METHODS

A modified, binocular video slit lamp interfaced to a personal computer and framegrabber allows for image acquisition and rendering of stored images overlaid onto the real-time slit-lamp biomicroscopic fundus image. Development proceeds with rendering on a computer monitor, while construction is completed on a miniature display interfaced directly with one of the slit-lamp oculars. Registration and tracking are performed with in-house-developed software.

MAIN OUTCOME MEASURES

Tracking speed and accuracy, ergonomic acceptability.

RESULTS

Computer-vision algorithms permit robust montaging, tracking, registration, and rendering of previously stored photographic and angiographic images onto the real-time slit-lamp fundus biomicroscopic image. In model eyes and in preliminary studies in a human eye, optimized registration permits near-video-rate image overlay with updates at 3 to 10 Hz and misregistration errors on the order of 1 to 5 pixels.

CONCLUSIONS

A prototype for ophthalmic augmented reality (image overlay) is presented. The current hardware/software implementation allows for robust performance.