Color vision impairment in type 2 diabetes assessed by the D-15d test and the Cambridge Colour Test

Color vision impairment emerges at early stages of diabetes mellitus type 2 (DM2) and may precede diabetic retinopathy or the appearance of vascular alterations in the retina. The aim of the present study was to compare the evaluation of the color vision with two different tests - the Lanthony desaturated D-15d test (a traditional color arrangement test), and the Cambridge Colour Test (CCT) (a computerized color discrimination test) - in patients diagnosed with DM2 without clinical signs of diabetic retinopathy (DR), and in sex- and age-matched control groups. Both color tests revealed statistically significant differences between the controls and the worst eyes of the DM2 patients. In addition, the degree of color vision impairment diagnosed by both tests correlated with the disease duration. The D-15d outcomes indicated solely tritan losses. In comparison, CCT outcomes revealed diffuse losses in color discrimination: 13.3% for best eyes and 29% for worst eyes. In addition, elevation of tritan thresholds in the DM2 patients, as detected by the Trivector subtest of the CCT, was found to correlate with the level of glycated hemoglobin. Outcomes of both tests confirm that subclinical losses of color vision are present in DM2 patients at an early stage of the disease, prior to signs of retinopathy. Considering the advantages of the CCT test compared to the D-15d test, further studies should attempt to verify and/or improve the efficiency of the CCT test.

A computer-controlled color vision test for children based on the Cambridge Colour Test

The present study aimed at providing conditions for the assessment of color discrimination in children using a modified version of the Cambridge Colour Test (CCT, Cambridge Research Systems Ltd., Rochester, UK). Since the task of indicating the gap of the Landolt C used in that test proved counterintuitive and/or difficult for young children to understand, we changed the target Stimulus to a patch of color approximately the size of the Landolt C gap (about 7 degrees Of Visual angle at 50 cm from the monitor). The modifications were performed for the CCT Trivector test which measures color discrimination for the protan, deutan and tritan confusion lines. Experiment I Sought to evaluate the correspondence between the CCT and the child-friendly adaptation with adult subjects (n = 29) with normal color vision. Results showed good agreement between the two test versions. Experiment 2 tested the child-friendly software with children 2 to 7 years old (n = 25) using operant training techniques for establishing and maintaining the subjects` performance. Color discrimination thresholds were progressively lower as age increased within the age range tested (2 to 30 years old), and the data-including those obtained for children-fell within the range of thresholds previously obtained for adults with the CCT. The protan and deutan thresholds were consistently lower than tritan thresholds, a pattern repeatedly observed in adults tested with the CCT. The results demonstrate that the test is fit for assessment of color discrimination in young children and may be a useful tool for the establishment of color vision thresholds during development.

Chromatic discrimination losses in multiple sclerosis patients with and without optic neuritis using the Cambridge Colour Test

We assessed chromatic discrimination in multiple sclerosis (MS) patients both with (ON) and without (no ON) a history of optic neuritis using the Cambridge color test (CCT). Our goal was to determine the magnitude and chromatic axes of any color vision losses in both patient groups, and to evaluate age-related changes in chromatic discrimination in both patient groups compared to normals. Using the CCT, we measured chromatic discrimination along the protan, deutan and tritan axes in 35 patients with MS (17 ON eyes) and 74 age matched controls. Color thresholds for both patient groups were significantly higher than controls` along the protan and tritan axes (P < 0.001). In addition, the ON and no-ON groups differed significantly along all three-color axes (p < 0.001). MS patients presented a progressive color discrimination impairment with age (along the deutan and tritan axes) that was almost two times faster than controls, even in the absence of ON. These findings suggest that demyelinating diseases reduce sensitivity to color vision in both red-green and blue-yellow axes, implying impairment in both parvocellular and koniocellular visual pathways. The CCT is a useful tool to help characterize vision losses in MS and the relationship between these losses and degree of optic nerve involvement.

Riverbed: A Novel User-Steered Image Segmentation Method Based on Optimum Boundary Tracking

This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths.

Probing the anomalous extinction of four young star clusters: the use of colour-excess, main-sequence fitting and fractal analysis

Aims. We studied four young star clusters to characterise their anomalous extinction or variable reddening and asses whether they could be due to contamination by either dense clouds or circumstellar effects. Methods. We evaluated the extinction law (R-V) by adopting two methods: (i) the use of theoretical expressions based on the colour-excess of stars with known spectral type; and (ii) the analysis of two-colour diagrams, where the slope of the observed colour distribution was compared to the normal distribution. An algorithm to reproduce the zero-age main-sequence (ZAMS) reddened colours was developed to derive the average visual extinction (A(V)) that provides the closest fit to the observational data. The structure of the clouds was evaluated by means of a statistical fractal analysis, designed to compare their geometric structure with the spatial distribution of the cluster members. Results. The cluster NGC 6530 is the only object of our sample affected by anomalous extinction. On average, the other clusters suffer normal extinction, but several of their members, mainly in NGC 2264, seem to have high R-V, probably because of circumstellar effects. The ZAMS fitting provides A(V) values that are in good agreement with those found in the literature. The fractal analysis shows that NGC 6530 has a centrally concentrated distribution of stars that differs from the substructures found in the density distribution of the cloud projected in the A(V) map, suggesting that the original cloud was changed by the cluster formation. However, the fractal dimension and statistical parameters of Berkeley 86, NGC 2244, and NGC 2264 indicate that there is a good cloud-cluster correlation, when compared to other works based on an artificial distribution of points.

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

Influence of artificial accelerated ageing on the colour stability of paints used for ocular prosthesis iris painting

Objectives: To evaluate the colour stability of paints used for ocular prosthesis iris painting submitted for accelerated artificial ageing (AAA). Materials and methods: Forty specimens of acrylic resin for sclera (16 x 2 mm) were made and separated into eight groups (n = 10) according to the type of paint (gouache, GP; oil, OP; acrylic AP; and composite resin for characterisation, CR) and the colours used (blue/brown). After drying (72 h), a new layer of colourless acrylic resin was applied and the initial colour readout was performed (Spectrophotometer PCB 6807). New colour readouts were performed after AAA, and Delta E was calculated. Results: Statistical analysis (two-way ANOVA-Bonferroni, p < 0.05) demonstrated that the brown colour showed lower Delta E means in comparison with the blue colour, with statistically significant difference for AP only. Blue colour showed no statistically significant difference with regard to the type of paint used. Brown AP showed lower Delta E than the other groups, with significant difference for OP and GP. GP showed greater alteration in Delta E for the brown colour, being statistically similar only to OP. Conclusions: Only the AP group for brown pigment shows clinically acceptable values for colour stability after AAA.

Milky Way demographics with the VVV survey I. The 84-million star colour-magnitude diagram of the Galactic bulge

Context. The Milky Way (MW) bulge is a fundamental Galactic component for understanding the formation and evolution of galaxies, in particular our own. The ESO Public Survey VISTA Variables in the Via Lactea is a deep near-IR survey mapping the Galactic bulge and southern plane. Particularly for the bulge area, VVV is covering similar to 315 deg(2). Data taken during 2010 and 2011 covered the entire bulge area in the JHKs bands. Aims. We used VVV data for the whole bulge area as a single and homogeneous data set to build for the first time a single colour-magnitude diagram (CMD) for the entire Galactic bulge. Methods. Photometric data in the JHK(s) bands were combined to produce a single and huge data set containing 173 150 467 sources in the three bands, for the similar to 315 deg(2) covered by VVV in the bulge. Selecting only the data points flagged as stellar, the total number of sources is 84 095 284. Results. We built the largest colour-magnitude diagrams published up to date, containing 173.1+ million sources for all data points, and more than 84.0 million sources accounting for the stellar sources only. The CMD has a complex shape, mostly owing to the complexity of the stellar population and the effects of extinction and reddening towards the Galactic centre. The red clump (RC) giants are seen double in magnitude at b similar to -8 degrees-10 degrees, while in the inner part (b similar to -3 degrees) they appear to be spreading in colour, or even splitting into a secondary peak. Stellar population models show the predominance of main-sequence and giant stars. The analysis of the outermost bulge area reveals a well-defined sequence of late K and M dwarfs, seen at (J - K-s) similar to 0.7-0.9 mag and K-s greater than or similar to 14 mag. Conclusions. The interpretation of the CMD yields important information about the MW bulge, showing the fingerprint of its structure and content. We report a well-defined red dwarf sequence in the outermost bulge, which is important for the planetary transit searches of VVV. The double RC in magnitude seen in the outer bulge is the signature of the X-shaped MW bulge, while the spreading of the RC in colour, and even its splitting into a secondary peak, are caused by reddening effects. The region around the Galactic centre is harder to interpret because it is strongly affected by reddening and extinction.

Bilayer segmentation of live video in uncontrolled environments for background substitution: an overview and main challenges

Bilayer segmentation of live video in uncontrolled environments is an essential task for home applications in which the original background of the scene must be replaced, as in videochats or traditional videoconference. The main challenge in such conditions is overcome all difficulties in problem-situations (e. g., illumination change, distract events such as element moving in the background and camera shake) that may occur while the video is being captured. This paper presents a survey of segmentation methods for background substitution applications, describes the main concepts and identifies events that may cause errors. Our analysis shows that although robust methods rely on specific devices (multiple cameras or sensors to generate depth maps) which aid the process. In order to achieve the same results using conventional devices (monocular video cameras), most current research relies on energy minimization frameworks, in which temporal and spacial information are probabilistically combined with those of color and contrast.

Automatic lumen segmentation in IVOCT images using binary morphological reconstruction

Abstract Background Atherosclerosis causes millions of deaths, annually yielding billions in expenses round the world. Intravascular Optical Coherence Tomography (IVOCT) is a medical imaging modality, which displays high resolution images of coronary cross-section. Nonetheless, quantitative information can only be obtained with segmentation; consequently, more adequate diagnostics, therapies and interventions can be provided. Since it is a relatively new modality, many different segmentation methods, available in the literature for other modalities, could be successfully applied to IVOCT images, improving accuracies and uses. Method An automatic lumen segmentation approach, based on Wavelet Transform and Mathematical Morphology, is presented. The methodology is divided into three main parts. First, the preprocessing stage attenuates and enhances undesirable and important information, respectively. Second, in the feature extraction block, wavelet is associated with an adapted version of Otsu threshold; hence, tissue information is discriminated and binarized. Finally, binary morphological reconstruction improves the binary information and constructs the binary lumen object. Results The evaluation was carried out by segmenting 290 challenging images from human and pig coronaries, and rabbit iliac arteries; the outcomes were compared with the gold standards made by experts. The resultant accuracy was obtained: True Positive (%) = 99.29 ± 2.96, False Positive (%) = 3.69 ± 2.88, False Negative (%) = 0.71 ± 2.96, Max False Positive Distance (mm) = 0.1 ± 0.07, Max False Negative Distance (mm) = 0.06 ± 0.1. Conclusions In conclusion, by segmenting a number of IVOCT images with various features, the proposed technique showed to be robust and more accurate than published studies; in addition, the method is completely automatic, providing a new tool for IVOCT segmentation.

Computerized brain tumor segmentation in magnetic resonance imaging

OBJECTIVE: To propose an automatic brain tumor segmentation system. METHODS: The system used texture characteristics as its main source of information for segmentation. RESULTS: The mean correct match was 94% of correspondence between the segmented areas and ground truth. CONCLUSION: Final results showed that the proposed system was able to find and delimit tumor areas without requiring any user interaction.

Horse spleen segmentation technique as large animal model of preclinical trials

The parenchymal distribution of the splenic artery was studied in order to obtain anatomical basis for partial splenectomy. Thirty two spleens were studied, 26 spleens of healthy horses weighing 320 to 450kg, aged 3 to 12 years and 6 spleens of fetus removed from slaughterhouse. The spleens were submitted to arteriography and scintigraphy in order to have their vascular pattern examined and compared to the external aspect of the organ aiming establish anatomo-surgical segments. All radiographs were photographed with a digital camera and the digital images were submitted to a measuring system for comparative analysis of areas of dorsal and ventral anatomo-surgical segments. Anatomical investigations into the angioarchitecture of the equine spleen showed a paucivascular area, which coincides with a thinner external area, allowing the organ to be divided in two anatomo-surgical segments of approximately 50% of the organ each.

Effects of low-salinity and high-turbidity waters one mpirical ocean colour algorithms: an example for Southwestern Atlantic waters

The spectral reflectance of the sea surface recorded using ocean colour satellite sensors has been used to estimate chlorophyll-a concentrations for decades. However, in bio-optically complex coastal waters, these estimates are compromised by the presence of several other coloured components besides chlorophyll, especially in regions affected by low-salinity waters. The present work aims to (a) describe the influence of the freshwater plume from the La Plata River on the variability of in situ remote sensing reflectance and (b) evaluate the performance of operational ocean colour chlorophyll algorithms applied to Southwestern Atlantic waters, which receive a remarkable seasonal contribution from La Plata River discharges. Data from three oceanographic cruises are used, in addition to a historical regional bio-optical dataset. Deviations found between measured and estimated concentrations of chlorophyll-a are examined in relation to surface water salinity and turbidity gradients to investigate the source of errors in satellite estimates of pigment concentrations. We observed significant seasonal variability in surface reflectance properties that are strongly driven by La Plata River plume dynamics and arise from the presence of high levels of inorganic suspended solids and coloured dissolved materials. As expected, existing operational algorithms overestimate the concentration of chlorophyll-a, especially in waters of low salinity (S<33.5) and high turbidity (Rrs(670)>0.0012 sr−1). Additionally, an updated version of the regional algorithm is presented, which clearly improves the chlorophyll estimation in those types of coastal environment. In general, the techniques presented here allow us to directly distinguish the bio-optical types of waters to be considered in algorithm studies by the ocean colour community.

Dynamic texture segmentation based on deterministic partially self-avoiding walks

Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.

Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks

Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.