Automated analysis of differential interference contrast microscopy images of the foveal cone mosaic

Wojtas, David H.; Wu, Bing; Ahnelt, Peter K.; Bones, Philip J.; Millane, Rick P.

doi:10.1364/josaa.25.001181

Cited by 26 publications

(20 citation statements)

References 37 publications

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“…Investigation of the preferred packing arrangement of rods in the retinal periphery could add valuable information about their normal distribution in the healthy retina [4]. A third issue is that analysis was performed only along the horizontal retinal meridian; the effect of sampling windows size and orientation could be influenced by local variance of the photoreceptor mosaic as a consequence of its different expansion between the horizontal and vertical meridians [10,18,24,38,39]. If the results of the present work were extended to the vertical meridian, it is very likely that the vertical oriented windows had a higher cone density than the horizontal ones.…”

Section: Discussionmentioning

confidence: 99%

Influence of sampling window size and orientation on parafoveal cone packing density

Lombardo

Serrao

Ducoli

et al. 2013

Biomed. Opt. Express

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Abstract:We assessed the agreement between sampling windows of different size and orientation on packing density estimates in images of the parafoveal cone mosaic acquired using a flood-illumination adaptive optics retinal camera. Horizontal and vertical oriented sampling windows of different size (320x160 µm, 160x80 µm and 80x40 µm) were selected in two retinal locations along the horizontal meridian in one eye of ten subjects. At each location, cone density tended to decline with decreasing sampling area. Although the differences in cone density estimates were not statistically significant, Bland-Altman plots showed that the agreement between cone density estimated within the different sampling window conditions was moderate. The percentage of the preferred packing arrangements of cones by Voronoi tiles was slightly affected by window size and orientation. The results illustrated the high importance of specifying the size and orientation of the sampling window used to derive cone metric estimates to facilitate comparison of different studies.

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Section: Discussionmentioning

confidence: 99%

Influence of sampling window size and orientation on parafoveal cone packing density

Lombardo

Serrao

Ducoli

et al. 2013

Biomed. Opt. Express

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“…Overall, the foveal mosaic is a highly regular nearly crystalline lattice with predominant 1:6 (hexagonal) neighborship relations. However previous detailed packing analyses [35,36,37] have revealed lattice discontinuities represented by cone positions with < 6 > cone neighbors subdividing the hexagonal mosaic in patchy. In a rhesus monkey foveal mosaic with labeled S-cones these positions with irregular number of neighbors have been identified in a previous study [35].…”

Section: S-cone Positions Vs Irregular Positions Among the Otherwise mentioning

confidence: 94%

“…Such mosaics had been previously analyzed with respect to lattice regularity [35,36,37] but there had been no approach to quantitatively study a possible relationship between S-cone positions and non-hexagonal defects of the M/L-cone lattice. In this last experiment we wanted to analyze the spatial relationships of Scones with a specific feature of foveal microarchitecture.…”

Section: S-cone Positions Vs Irregular Positions Among the Otherwise mentioning

confidence: 99%

V-Proportion: A method based on the Voronoi diagram to study spatial relations in neuronal mosaics of the retina

Mozos¹,

Bolea²,

Ferrández³

et al. 2010

Neurocomputing

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The visual system plays a predominant role in the human perception. Although all components of the eye are important to perceive visual information, the retina is a fundamental part of the visual system. In this work we study the spatial relations between neuronal mosaics in the retina. These relations have shown its importance to investigate possible constraints or connectivities between different spatially colocalized populations of neurons, and to explain how visual information spreads along the layers before being sent to the brain. We introduce the V-Proportion, a method based on the Voronoi diagram to study possible spatial interactions between two neuronal mosaics. Results in simulations as well as in real data demonstrate the effectiveness of this method to detect spatial relations between neurons in different layers.

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“…However, despite individual differences in cone density and spacing, the parafoveal cone mosaic uniformly presents as a triangular lattice, and it is thought that the quality of the cone lattice is of high importance for the interreceptoral network and cell signaling (Hirsch & Miller, 1987; Pum et al , 1990; Lombardo et al , 2013b). Thus, disorder in cone packing could serve as an important and sensitive measure with which to characterize a given image of the cone mosaic (Baraas et al , 2007; Wojtas et al , 2008). …”

Section: Introductionmentioning

confidence: 99%

Methods for investigating the local spatial anisotropy and the preferred orientation of cones in adaptive optics retinal images

et al. 2016

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The ability to non-invasively image the cone photoreceptor mosaic holds significant potential as a diagnostic for retinal disease. Central to the realization of this potential is the development of sensitive metrics for characterizing the organization of the mosaic. Here we evaluated previously-described (Pum et al., 1990) and newly-developed (Fourier- and Radon-based) methods of measuring cone orientation in both simulated and real images of the parafoveal cone mosaic. The proposed algorithms correlated well across both simulated and real mosaics, suggesting that each algorithm would provide an accurate description of individual photoreceptor orientation. Despite the high agreement between algorithms, each performed differently in response to image intensity variation and cone coordinate jitter. The integration property of the Fourier transform allowed the Fourier-based method to be resistant to cone coordinate jitter and perform the most robustly of all three algorithms. Conversely, when there is good image quality but unreliable cone identification, the Radon algorithm performed best. Finally, in cases where both the image and cone coordinate reliability was excellent, the method of Pum et al. (1990) performed best. These descriptors are complementary to conventional descriptive metrics of the cone mosaic, such as cell density and spacing, and have the potential to aid in the detection of photoreceptor pathology.

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Automated analysis of differential interference contrast microscopy images of the foveal cone mosaic

Cited by 26 publications

References 37 publications

Influence of sampling window size and orientation on parafoveal cone packing density

Influence of sampling window size and orientation on parafoveal cone packing density

V-Proportion: A method based on the Voronoi diagram to study spatial relations in neuronal mosaics of the retina

Methods for investigating the local spatial anisotropy and the preferred orientation of cones in adaptive optics retinal images

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