Segmentation of retinal layers from OCT images is fundamental to diagnose the progress of retinal diseases. In this study we show that the retinal layers can be automatically and/or interactively located with good accuracy with the aid of local coherence information of the retinal structure. OCT images are processed using the ideas of texture analysis by means of the structure tensor combined with complex diffusion filtering. Experimental results indicate that our proposed novel approach has good performance in speckle noise removal, enhancement and segmentation of the various cellular layers of the retina using the STRATUSOCTTM system.

A comparison between two nonlinear diffusion methods for denoising OCT images is performed. Specifically, we compare and contrast the performance of the traditional nonlinear Perona-Malik filter with a complex diffusion filter that has been recently introduced by Gilboa et al.. The complex diffusion approach based on the generalization of the nonlinear scale space to the complex domain by combining the diffusion and the free Schridinger equation is evaluated on synthetic images and also on representative OCT images at various noise levels. The performance improvement over the traditional nonlinear Perona-Malik filter is quantified in terms of noise suppression, image structural preservation and visual quality. An average signal-to-noise ratio (SNR) improvement of about 2.5 times and an average contrast to noise ratio (CNR) improvement of 49% was obtained while mean structure similarity (MSSIM) was practically not degraded after denoising. The nonlinear complex diffusion filtering can be applied with success to many OCT imaging applications. In summary, the numerical values of the image quality metrics along with the qualitative analysis results indicated the good feature preservation performance of the complex diffusion process, as desired for better diagnosis in medical imaging processing.

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We have shown that it is feasible to perform penile transplantation with excellent results. Furthermore, this experience demonstrates that penile transplantation can be successfully performed with conventional immunosuppression. We propose that our successful penile transplantation pilot experience represents a proof of concept for an evolution in reconstructive transplantation.

The development of improved segmentation algorithms for more consistently accurate detection of retinal boundaries is a potentially useful solution to the limitations of existing optical coherence tomography (OCT) software. We modeled artifacts related to operator errors that may normally occur during OCT imaging and evaluated their influence on segmentation results using a novel segmentation algorithm. These artifacts included: defocusing, depolarization, decentration, and a combination of defocusing and depolarization. Mean relative reflectance and average thickness of the automatically extracted intraretinal layers was then measured. Our results show that defocusing and depolarization errors together have the greatest altering effect on all measurements and on segmentation accuracy. A marked decrease in mean relative reflectance and average thickness was observed due to depolarization artifact in all intraretinal layers, while defocus resulted in a less-marked decrease. Decentration resulted in a marked but not significant change in average thickness. Our study demonstrates that care must be taken for good-quality imaging when measurements of intraretinal layers using the novel algorithm are planned in future studies. An awareness of these pitfalls and their possible solutions is crucial for obtaining a better quantitative analysis of clinically relevant features of retinal pathology.