Automatic generation of synthetic retinal fundus images:Vascular network

AbstractThis work is part of an ongoing project aimed to generate synthetic retinal fundus images. This paper concentrates on the generation of synthetic vascular networks with realistic shape and texture characteristics. An example-based method, the Active Shape Model, is used to synthesize reliable vessels’ shapes. An approach based on Kalman Filtering combined with an extension of the Multiresolution Hermite vascular cross-section model has been developed for the simulation of vessels’ textures. The proposed method is able to generate realistic synthetic vascular networks with morphological properties that guarantee the correct flow of the blood and the oxygenation of the retinal surface observed by fundus cameras. The validity of our synthetic retinal images is demonstrated by qualitative assessment and quantitative analysis

Features of the normal choriocapillaris with OCT-angiography: Density estimation and textural properties

The main objective of our work is to perform an in depth analysis of the structural features of normal choriocapillaris imaged with OCT Angiography. Specifically, we provide an optimal radius for a circular Region of Interest (ROI) to obtain a stable estimate of the subfoveal choriocapillaris density and characterize its textural properties using Markov Random Fields. On each binarized image of the choriocapillaris OCT Angiography we performed simulated measurements of the subfoveal choriocapillaris densities with circular Regions of Interest (ROIs) of different radii and with small random displacements from the center of the Foveal Avascular Zone (FAZ). We then calculated the variability of the density measure with different ROI radii. We then characterized the textural features of choriocapillaris binary images by estimating the parameters of an Ising model. For each image we calculated the Optimal Radius (OR) as the minimum ROI radius required to obtain a standard deviation in the simulation below 0.01. The density measured with the individual OR was 0.52 ± 0.07 (mean ± STD). Similar density values (0.51 ± 0.07) were obtained using a fixed ROI radius of 450 μm. The Ising model yielded two parameter estimates (β = 0.34 ± 0.03; γ = 0.003 ± 0.012; mean ± STD), characterizing pixel clustering and white pixel density respectively. Using the estimated parameters to synthetize new random textures via simulation we obtained a good reproduction of the original choriocapillaris structural features and density. In conclusion, we developed an extensive characterization of the normal subfoveal choriocapillaris that might be used for flow analysis and applied to the investigation pathological alterations

Comparative analysis of retinal photoplethysmographic spatial maps and thickness of retinal nerve fiber layer.

The paper presents a comparative study of the pulsatile attenuation amplitude (PAA) within the optic nerve head (ONH) at four different areas calculated from retinal video sequences and its relevance to the retinal nerve fiber layer thickness (RNFL) changes in normal subjects and patients with different stages of glaucoma. The proposed methodology utilizes processing of retinal video sequences acquired by a novel video ophthalmoscope. The PAA parameter measures the amplitude of heartbeat-modulated light attenuation in retinal tissue. Correlation analysis between PAA and RNFL is performed in vessel-free locations of the peripapillary region with the proposed evaluating patterns: 360° circular area, temporal semi-circle, nasal semi-circle. For comparison, the full ONH area is also included. Various positions and sizes of evaluating patterns in peripapillary region were tested which resulted in different outputs of correlation analysis. The results show significant correlation between PAA and RNFL thickness calculated in proposed areas. The highest correlation coefficient Rtemp = 0.557 (p<0.001) reflects the highest PAA-RNFL correspondence in the temporal semi-circular area, compared to the lowest value in the nasal semi-circular area (Rnasal = 0.332, p<0.001). Furthermore, the results indicate the most relevant approach to calculate PAA from the acquired video sequences is using a thin annulus near the ONH center. Finally, the paper shows the proposed photoplethysmographic principle based on innovative video ophthalmoscope can be used to analyze changes in retinal perfusion in peripapillary area and can be potentially used to assess progression of the RNFL deterioration

Retinal photoplethysmography study dataset

The dataset is related to PLOS ONE article: "Odstrcilik, J., et al. Comparative analysis of retinal photoplethysmographic spatial maps and thickness of retinal nerve fiber layer." Each file is stored in Matlab memory format (*.MAT), which can be loaded either directly via MATLAB computing software or alternatively in Python programming software. File description: PAA_original_maps_plosone.mat  - image matrices (format: double), each for a single subject involved in the study Blood_vessels_BW_templates_plosone.mat  - image matrices (format: binary), each for a single subject involved in the study ONH_BW_templates_plosone.mat  - image matrices (format: binary), each for a single subject involved in the study RNFL_circular_OCT_scans_plosone.mat  - matrix (format: double) with RNFL circular scans for a single subject involved in the study Diagnoses_key_plosone.mat  - diagnoses key - a vector of diagnoses groups (format: integer) for a single subject involved in the study For more information, please refer to respective article in PLOS ONE journal or contact the author.</p

2D and 3D vascular structures enhancement via multiscale fractional anisotropy tensor

The detection of vascular structures from noisy images is a fundamental process for extracting meaningful information in many applications. Most well-known vascular enhancing techniques often rely on Hessian-based filters. This paper investigates the feasibility and deficiencies of detecting curve-like structures using a Hessian matrix. The main contribution is a novel enhancement function, which overcomes the deficiencies of established methods. Our approach has been evaluated quantitatively and qualitatively using synthetic examples and a wide range of real 2D and 3D biomedical images. Compared with other existing approaches, the experimental results prove that our proposed approach achieves high-quality curvilinear structure enhancement.Comment: ECCV 2018 Workshops,Munich, Germany, Sept. 201