Alfredo Ruggeri

Detection of optic disc in retinal images by means of a geometrical model of vessel structure

We present here a new method to identify the position of the optic disc (OD) in retinal fundus images. The method is based on the preliminary detection of the main retinal vessels. All retinal vessels originate from the OD and their path follows a similar directional pattern (parabolic course) in all images. To describe the general direction of retinal vessels at any given position in the image, a geometrical parametric model was proposed, where two of the model parameters are the coordinates of the OD center. Using as experimental data samples of vessel centerline points and corresponding vessel directions, provided by any vessel identification procedure, model parameters were identified by means of a simulated annealing optimization technique. These estimated values provide the coordinates of the center of OD. A Matlab/spl reg/ prototype implementing this method was developed. An evaluation of the proposed procedure was performed using the set of 81 images from the STARE project, containing images from both normal and pathological subjects. The OD position was correctly identified in 79 out of 81 images (98%), even in rather difficult pathological situations.

Luminosity and contrast normalization in retinal images.

Retinal images are routinely acquired and assessed to provide diagnostic evidence for many important diseases, e.g. diabetes or hypertension. Because of the acquisition process, very often these images are non-uniformly illuminated and exhibit local luminosity and contrast variability. This problem may seriously affect the diagnostic process and its outcome, especially if an automatic computer-based procedure is used to derive diagnostic parameters. We propose here a new method to normalize luminosity and contrast in retinal images, both intra- and inter-image. The method is based on the estimation of the luminosity and contrast variability in the background part of the image and the subsequent compensation of this variability in the whole image. The application of this method on 33 fundus images showed an average 19% (max. 45%) reduction of luminosity variability and an average 34% (max. 85%) increment of image contrast, with a remarkable improvement, e.g., over low-pass correction. The proposed image normalization technique will definitely improve automatic fundus images analysis but will also be very useful to eye specialists in their visual examination of retinal images.

A divide et impera strategy for automatic classification of retinal vessels into arteries and veins

The first pathologic alterations of the retina are seen in the vessel network. These modifications affect very differently arteries and veins, and the appearance and entity of the modification differ as the retinopathy becomes milder or more severe. In order to develop an automatic procedure for the diagnosis and grading of retinopathy, it is necessary to be able to discriminate arteries from veins. The problem is complicated by the similarity in the descriptive features of these two structures and by the contrast and luminosity variability of the retina. We developed a new algorithm for classifying the vessels, which exploits the peculiarities of retinal images. By applying a divide et impera approach that partitioned a concentric zone around the optic disc into quadrants, we were able to perform a more robust local classification analysis. The results obtained by the proposed technique were compared with those provided by a manual classification on a validation set of 443 vessels and reached an overall classification error of 12%, which reduces to 7% if only the diagnostically important retinal vessels are considered.

Visceral adipose tissue impairs insulin secretion and insulin sensitivity but not energy expenditure in obesity

In obesity, a central pattern of fat distribution is mostly associated with hyperinsulinemia, insulin resistance, and hyperlipemia, thus promoting the development of non-insulin-dependent diabetes mellitus and cardiovascular disease. In addition, in obesity, changes in energy expenditure are hypothesized to be involved in the development or maintenance of excessive body fat storage. In this study, abdominal fat distribution by computed tomographic (CT) scan was used to study the relation between the visceral fat depot, insulin secretion, and insulin sensitivity in a group of obese subjects with normal glucose tolerance (n = 26; body mass index [BMI], 39 +/- 1 kg/m2) and a group of normal-weight control subjects (n = 9; BMI, 23 +/- 1 kg/m2). The minimal model method was used to assess insulin sensitivity, S(I), and first-phase (phi1) and second-phase (phi2) beta-cell sensitivity from plasma glucose, insulin, and C-peptide concentrations measured during an intravenous glucose tolerance test ([IVGTT] 0.33 g/kg body weight). Moreover, we evaluated the relationships between these parameters and the resting metabolic rate (RMR) and glucose-induced thermogenesis (GIT) measured by indirect calorimetry. The data show the following: (1) in obese subjects, phi1 is greater but not statistically different from the value in control subjects (252 +/- 41 v 157 +/- 25 dimensionless 10(9)); (2) phi2 is significantly higher in obese subjects (27 +/- 4 v 14 +/- 2 min(-1) x 10(9), P < .05), with a positive correlation between the amount of visceral adipose tissue (VAT) and phi2 (r = .49, P < .05); (3) S(I) is decreased in the obese group (2.8 +/- 0.3 v 9.7 +/- 1.6 10(-4) x min(-1)/microU x mL(-1)), P < .0001), with a negative correlation of S(I) with the adiposity index BMI (r = -.67, P < .0001) and VAT (r = .56, P < .05); (4) RMR, expressed in absolute terms, was significantly increased in obese versus lean subjects (5.9 +/- 0.2 v 4.6 +/- 0.3 kJ/min, P < .01), whereas when RMR was adjusted for fat-free mass (FFM), the difference between the two groups disappeared (0.09 +/- 0.003 v 0.09 +/- 0.002 kJ/min x kg FFM). We did not observe any difference in GIT between lean and obese subjects. Moreover, GIT was significantly correlated with FFM (r = .69, P < .005), but not with BMI. The amount of VAT did not correlate with RMR or GIT. In conclusion, these results suggest that in obese subjects with normal glucose tolerance, insulin sensitivity is impaired and the beta-cell hyperresponse to glucose is mainly due to an enhanced second-phase beta-cell secretion. The degree of visceral fat deposition seems to affect insulin secretion and worsens insulin sensitivity, but does not influence energy expenditure.

Evaluation of Portal/Peripheral Route and of Algorithms for Insulin Delivery in the Closed-Loop Control of Glucose in Diabetes - A Modeling Study

In this paper we present an evaluation of portal versus peripheral routes for insulin delivery in diabetes with three representative closed-loop glucose control algorithms. A novel noninvasive approach is used which is based on a model of the blood glucose regulation system which simulates a Type I diabetic subject. The two routes and three algorithms are compared in controlling the simulated patient for 24 h, challenged with two dynamic glucose perturbations. The evaluation is performed by comparing both plasma accessible variables (e.g., glucose and insulin) and metabolic fluxes (e.g., glucose production and uptake, peripheral glucose utilization). Similar performances are achieved by the three algorithms both with peripheral and with portal infusions, especially in the postabsorptive steady state. An almost complete metabolic normalization is obtained with the portal route. With the peripheral route, normality is not restored; in particular, hyperinsulinemia and enhanced insulin-dependent glucose utilization are produced. From these simulation results, it is the site of insulin infusion, which appears to play an essential role in terms of the ability to normalize the metabolic state of a diabetic subject.

Automatic Recognition of Corneal Nerve Structures in Images from Confocal Microscopy

PURPOSE To devise a method for automatically tracing corneal nerves in confocal microscopy images. METHODS Images were acquired with a confocal microscope. They were normalized and enhanced in luminosity and contrast. The nerves were recognized by applying a novel tracing algorithm, which includes Gabor filtering to enhance nerve visibility and postprocessing procedures to remove false recognitions and to link sparse segments into continuous structures. A prototype of the algorithm was implemented in commercial software and run on a personal computer. RESULTS A retrospective evaluation of the automatic procedure was performed on a data set containing 90 images, from normal and non-normal subjects. The average percentage of correctly recognized nerves length with respect to total manually traced lengths of visible nerves was 80.4% in normal subjects and 83.8% on non-normal subjects; the average rate of false nerve length recognition (with respect to the total automatically traced length) was 6.5% in normal subjects and 9.1% in non-normal subjects. Correlation coefficients between manual and automatic lengths on the same image were 0.94, 0.95, and 0.86 in all, normal, and non-normal subjects, respectively. A further evaluation was performed on an independent set of 80 normal subject images, resulting in a correlation coefficient of 0.89 between manual and automatic nerve lengths. CONCLUSIONS Automatic and manual length estimations on the same image were very well correlated, indicating that the automatic procedure is capable of correctly reproducing the differences in nerve length between different subjects.

Optimal Design of Multioutput Sampling Schedules - Software and Applications to Endocrine - Metabolic and Pharmacokinetic Models

This paper describes a program for computing optimal sampling schedules for multiinput-multioutput experiments designed for parameter estimation of physiological systems models. Theory of the algorithm and details of its implementation are given. Practical applications of the software to models of glucose-insulin regulation, ketone body, and insulin kinetics are presented. Results document the potentiality of the software for designing experiments, and show that optimal design can considerably reduce the number of samples withdrawn from a patient in in vivo clinical studies.

Validating retinal fundus image analysis algorithms: Issues and a proposal

This paper concerns the validation of automatic retinal image analysis (ARIA) algorithms. For reasons of space and consistency, we concentrate on the validation of algorithms processing color fundus camera images, currently the largest section of the ARIA literature. We sketch the context (imaging instruments and target tasks) of ARIA validation, summarizing the main image analysis and validation techniques. We then present a list of recommendations focusing on the creation of large repositories of test data created by international consortia, easily accessible via moderated Web sites, including multicenter annotations by multiple experts, specific to clinical tasks, and capable of running submitted software automatically on the data stored, with clear and widely agreed-on performance criteria, to provide a fair comparison.

Automatic Evaluation of Corneal Nerve Tortuosity in Images from In Vivo Confocal Microscopy

PURPOSE. An algorithm and a computer program for the automatic grading of corneal nerve tortuosity are proposed and evaluated. METHODS. Thirty images of the corneal subbasal nerve plexus with different grades of tortuosity were acquired with a scanning laser confocal microscope in normal and pathologic subjects. Nerves were automatically traced with an algorithm previously developed, and a tortuosity measure was computed with the proposed method, based on the number of changes in the curvature sign and on the amplitude (maximum distance of the curve from the underlying chord) of the nerve curves. These measures were evaluated according to their capability to reproduce the expert classification of images into three groups of tortuosity (low, mid, and high). This classification was also compared with measures provided by other methods proposed in the literature to evaluate nerve tortuosity. RESULTS. Among all considered methods, the one proposed herein allows a minimum of classification errors (only 2 in 30 images) and the highest Krippendorff concordance coefficient (0.96). Furthermore, it is the only one that can provide a significant difference (P < 0.01) between all pairs of tortuosity classes. CONCLUSIONS. The results provided by the proposed system confirmed its ability to perform a clinically significant evaluation of corneal nerve tortuosity.

Standardized Baseline Human Corneal Subbasal Nerve Density for Clinical Investigations With Laser-Scanning in Vivo Confocal Microscopy

PURPOSE We established a baseline value for central corneal subbasal nerve density in a large, healthy cohort. METHODS A total of 106 healthy volunteers (207 eyes) underwent full ophthalmic examination, including laser-scanning in vivo confocal microscopy (IVCM) of the central cornea. Images of the corneal subbasal nerve plexus were acquired and analyzed based on defined criteria. Nerve tracing was performed by two human observers and by a fully automated method. Subbasal nerve density was stratified by eye, observer, tracing method, calculation method, and age group. Association of nerve density with age was examined by linear regression and population distribution was examined by nonlinear regression. RESULTS We analyzed 892 distinct, high quality images of the subbasal nerve plexus (mean, 4.3 images/eye) from 207 eyes. An overall mean central subbasal nerve density of 19 mm/mm(2) was found in 106 subjects aged 15 to 88 years, independent of eye, sex, or nerve tracing method, while the SD was a consistent 4 to 5 mm/mm(2). Subbasal nerve density followed a normal Gaussian distribution, and correlated negatively with age, with a mean decline of 0.25% to 0.30% per year, independent of eye, observer, or nerve tracing method. Moreover, the use of automated tracing techniques and randomized sampling may improve the speed and reproducibility of subbasal nerve density assessment for clinical applications. CONCLUSIONS A baseline human corneal subbasal nerve density has been determined by laser-scanning IVCM using rigorous methods. The methods and results could aid in the future assessment of corneal nerves in various patient populations.