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Giovanni Gregori, Ph.D.

Giovanni Gregori, Ph.D.


Research Subject

Quantitative Ophthalmic Imaging


Retinal Imaging, Image Processing, Optical Coherence Tomography, Mathematical Modeling of Retinal Morphology and Disease Processes.

Published Articles


Research Associate Professor and Scientific Co-Director of The Experimental Imaging Laboratory


Dr. Gregori’s research involves developing mathematical models and algorithms to provide novel analyses of clinical and/or experimental data, particularly images acquired using Optical Coherence Tomography (OCT) technology. The goal is to advance the understanding of retinal morphology and the changes associated with ocular pathologies and/or treatment strategies, as well as to develop new quantitative strategies for the study of retinal diseases.

Current Research

In the last decade important technological advances have brought about a real revolution in the field of imaging in the eye, and our group at the Bascom Palmer Eye Institute (BPEI) has played an important role in this process. In 2004 Dr. Robert Knighton and Dr. Gregori formed the Quantitative Ophthalmic Imaging Group to focus on the development of new quantitative strategies to assess and study ocular diseases using the information generated by new imaging technologies, particularly the one known as Spectral Domain OCT. These instruments can produce three-dimensional, high resolution images of the retina and have become in a very short time an important tool both for clinical research and routine clinical care.

In 2005, Dr. Gregori was the first to develop fast and accurate three-dimensional segmentation algorithms for large OCT datasets and to show how these could be used to describe with unprecedented detail the spatial geometry and anatomy of the retina in vivo. Over the last few years Dr. Gregori’s group introduced several new powerful mathematical algorithms for processing large OCT datasets. These techniques were used to generate novel, reliable, quantitative information about the retinal geometry and its changes during the disease process. This is an important advancement as it made it possible to monitor and measure small changes in the retinal appearance, a crucial step both in understanding the mechanisms associated with a given pathology, as well as in evaluating the need for treatment or the effectiveness of different treatment regimes. This work has been the basis for several patent’s applications and licensing agreements between the University of Miami and Carl Zeiss Meditec, the leading manufacturer of commercial OCT instruments. Many of the algorithms and strategies developed by Dr. Gregori’s team have been implemented (or are in the process of being implemented) on commercially available OCT instruments and are now used routinely in the clinical care of patients.

A recent, noteworthy application of this work is the use of OCT datasets to advance our understanding of Age-related Macular Degeneration (AMD), the leading cause for severe visual loss in people over 65 years of age in developed countries. In particular we introduced tools to measure the progression of Geographic Atrophy and the effects of drusen on the Retinal Pigment Epithelium and the photoreceptors. Using these algorithms we were able to produce for the first time a detailed, quantitative description of drusen natural history. In collaboration with Dr. Philip Rosenfeld we showed that these measurements can be used as a surrogate clinical trial endpoint in studies designed to investigate treatments for non-exudative AMD. A number of clinical trials are currently underway, using our approach to test the effects of new potential therapies.

In 2009, Dr. Gregori was named the Scientific Co-Director of The Experimental Imaging Laboratory at Bascom Palmer Eye Institute.

Imaging large drusen with spectral domain optical coherence tomography (SDOCT)
Figure 1. Imaging large drusen with spectral domain optical coherence tomography (SDOCT). (From: G. Gregori et al., Spectral Domain Optical Coherence Tomography Imaging of Drusen in Non-Exudative Age-Related Macular Degeneration, Ophthalmology, 118, 1373-9, 2011).
A. A color fundus photo is shown with the superimposed location of the SDOCT dataset indicated by the blue square. This location can be determined with the help of the OCT fundus image.
B. Two B-scans are shown from the SDOCT that correspond to the white lines on the fundus photo. The segmentation of the retinal pigment epithelium (RPE) is shown in red and the drusen floor is shown in yellow.
C. Surface rendering of the RPE segmentation.
D. Retinal thickness map.
E. Drusen thickness map.