Bojidar Madjarov

Variability in fluorescein angiography interpretation for photodynamic therapy in age-related macular degeneration.

Objectives To investigate the variability in fluorescein angiography interpretation for photodynamic therapy in age-related macular degeneration. Methods Eight graders, who included two TAP-certified ophthalmologists, three other retinal specialists, two fellows in vitreoretinal diseases, and a senior fundus photograph grader, evaluated fluorescein angiograms of six patients treated according to the Treatment for ARMD With Verteporfin (TAP) protocol at a single center. Each patient’s baseline angiogram was evaluated to determine whether the CNV lesion was predominantly (≥50%) classic. For each follow-up angiogram, at 3, 6, 12, and 24 months, the grader was required to determine whether fluorescein leakage was present. Six months after the initial gradings, each reader was again presented with the baseline angiogram for each patient and once again asked to determine whether the CNV lesion was predominantly classic without knowledge of the previous grading. All gradings were performed without knowledge of the clinical course. Results In grading initial visit and follow-up visit angiograms, the overall concordance rates were 81% and 82%, respectively. Concordance rates were not statistically different between the group as a whole when compared with the gradings of the two TAP-certified ophthalmologists. When initial visit angiograms were regraded, an intraobserver variability of 17% was noted. Overall, gradings were discordant with the majority opinion in approximately 19% of decisions. Conclusions Considerable variability can be expected in fluorescein angiography interpretation as the results of the TAP investigation are applied to clinical practice.

Mosaicking and enhancement of slit lamp biomicroscopic fundus images

AIMS To process video slit lamp biomicroscopic fundus image sequences in order to generate wide field, high quality fundus image montages which might be suitable for photodocumentation. METHODS Slit lamp biomicroscopic fundus examination was performed on human volunteers with a contact or non-contact lens. A stock, charge coupled device camera permitted image capture and storage of the image sequence at 30 frames per second. Acquisition time was approximately 30 seconds. Individual slit lamp biomicroscope fundus image frames were aligned and blended with custom developed software. RESULTS The developed algorithms allowed for highly accurate alignment and blending of partially overlapping slit lamp biomicroscopic fundus images to generate a seamless, high quality, wide field montage. CONCLUSIONS Video image acquisition and processing algorithms allow for mosaicking and enhancement of slit lamp biomicroscopic fundus images. The improved quality and wide field of view may confer suitability for inexpensive, real time photodocumentation of disc and macular abnormalities.

Automated, real time extraction of fundus images from slit lamp fundus biomicroscope video image sequences.

AIMS Slit lamp fundus biomicroscopy allows for high magnification, stereoscopic diagnosis, and treatment of macular diseases. Variable contrast, narrow field of view, and specular reflections arising from the cornea, sclera, and examining lens reduce image quality; these images are of limited clinical utility for diagnosis, treatment planning, and photodocumentation when compared with fundus camera images. Algorithms are being developed to segment fundus imagery from slit lamp biomicroscopic video image sequences in order to improve clinical utility. METHODS Video fundus image sequences of human volunteers were acquired with a video equipped, Nikon NS-1V slit lamp biomicroscope. Custom developed software identified specular reflections based on brightness and colour content, and extracted the illuminated fundus image based on colour image analysis and size constraints. RESULTS In five subjects with variable image quality, the approach allowed for automatic, robust, accurate extraction of that portion of the video image corresponding to the illuminated portion of the fundus. Non-real time analysis allowed for fundus image segmentation for each frame of the image sequence. In real time, segmentation occurs at 2 Hz, and improvements are being implemented for video rate performance. CONCLUSIONS Computer vision algorithms allow for real time extraction of fundus imagery from marginal quality, slit lamp fundus biomicroscope image sequences.

Ophthalmic Slitlamp-Based Computer-Aided Diagnosis: Image Processing Foundations

Computer aided diagnosis and treatment of retinal disorders is enabled through an ophthalmic augmented reality environment being developed around the standard slitlamp biomicroscope. This system will allow the physician to view superimposed fundus photographic and angiographic data on the real-time slitlamp biomicroscopic image. The overlay capability requires real-time image acquisition, processing, mosaicking and comparison. Non-real time capabilities include the co-registration of similar or differing sources such as slitlamp biomicroscope, fundus photograph, or angiograms. Mosaicking enables the creation of montages from a collection of images and provides a context for robust registration and comparison. This paper outlines the image-processing architecture and controls to provide these functionalities.

Video injection for slit lamp augmented reality

Real-time tracking and overlay of previously stored photographic and angiographic images directly onto the real- time slitlamp biomicroscopic or surgical microscopic eye fundus image may facilitate real-time image comparison, measurement, and correlation for diagnosis, management and treatment of retinal diseases. Very high resolution and brightness is necessary to inject the overlayed image into the optical path of the diagnostic or surgical instrument. A binocular slit-lamp biomicroscope interfaced to a CCD camera, framegrabber board, and PC allows for posterior segment examination with a hand-held contact or non-contact lens, synchronous with acquisition and digitization of slitlamp fundus images.