Adaptive artificial retina model to improve perception quality of retina implant recipients

Karagöz, İrfan; Özden, Mustafa

doi:10.1109/bmei.2011.6098353

Cited by 2 publications

(7 citation statements)

References 18 publications

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“…In the simulation studies, the test images were processed by using our custom artificial retina model [24,25] and ganglion cell outputs for these images to be used as input data for STEMLIS and classical method were obtained. This section is organized into three subsections.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In the simulation study, it was assumed that the visual data to be stimulated were available in the form of encoded spike pulses by the artificial retina model. In this case, by using our custom artificial retina model [24,25], corresponding ganglion outputs previously obtained for test images. The stimulation data were then used in the implemented STEMLIS and classical method, and results of both models were analyzed.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal Electrode Mapping and Local Interleaved Stimulation Method (STEMLIS) for Artificial Sight Systems

Özden

Karagöz²

2015

J Bioengineer & Biomedical Sci

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Image processing algorithms play a key role in the development of visual prosthesis systems. In this study, a new electrode stimulation method for retinal implant systems, "Spatio-Temporal Electrode Mapping and Local Interleaved Stimulation (STEMLIS)," is proposed. In this method, the most meaningful spikes that preserve the spatial discrimination in a temporal frame are selected as stimulation data, and phase shifts are applied to all sub electrode groups to minimize undesired electrode interactions. By using this method, both spatial and temporal resolution of stimulation data can be enhanced, since spatio-temporal mapping is used while selecting the stimulation data from a large number of spike data for stimulation of the low-numbered electrode matrix placed on retina surface. The phase delays between the neighboring electrodes are used to introduce interleaved pulses, which minimize the electrical interactions. To evaluate the contribution of the STEMLIS method to perceived image quality, computer based quantitative simulation studies and visual evaluation tests with normal seeing people were performed. For quantitative evaluation, the outputs for the classical method and the STEMLIS method were compared based on the mean squared error (MSE), the histogram similarity ratio (HSR), and edge discrimination parameters. In visual tests, performance of the method was evaluated in terms of contrast discrimination, pattern recognition, text reading and object counting tasks. The subjects reached higher test scores with proposed method and better scores obtained in quantitative comparison. It is concluded that spatio-temporal enhancement of stimulation data can help to improve perceived image quality on visual prostheses.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Electrode Mapping and Local Interleaved Stimulation Method (STEMLIS) for Artificial Sight Systems

Özden

Karagöz²

2015

J Bioengineer & Biomedical Sci

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“…The typical cell resistance, time constant of the cell, and integration time constant are selected as 10 ohm, 5 ms, and 10 ms, respectively. Depending on the biological constants, the resting potential values (Vr ) and the firing threshold values (spk thr ) of the cells are selected as -65 mV and -50 mV, respectively [17,18].…”

Section: The Proposed Spatiotemporal Artificial Retina Model (3d-adog)mentioning

confidence: 99%

“…The proposed model has a 2-stage spatiotemporal filtering structure that is based on the inner cell layers of the biologic retina, and the interactions of both the receptor-horizontal and bipolar-amacrine cells are modeled using an adaptive DOG filter [17,18]. The nLIF cell model, which is a good approximation for modeling the firing mechanism of ganglion cells, is used for the realization of the spike generation process in artificial retina models.…”

Section: Introductionmentioning

confidence: 99%

“…In the present study, to overcome these disadvantages of the standard DOG filter-based retina models, a multistage DOG filter-based artificial retina model that changes the bandwidths of the DOG filters depending on the statistical characteristics of the local image data is proposed. The proposed model has a 2-stage spatiotemporal filtering structure that is based on the inner cell layers of the biologic retina, and the interactions of both the receptor-horizontal and bipolar-amacrine cells are modeled using an adaptive DOG filter [17,18]. The nLIF cell model, which is a good approximation for modeling the firing mechanism of ganglion cells, is used for the realization of the spike generation process in artificial retina models.…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal realization of an artificial retina model and performance evaluation through ISI- and spike count-based image reconstruction methods

Karagöz¹,

Özden²

2014

Turk J Elec Eng & Comp Sci

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Development of an artificial retina model that can mimic the biologic retina is a highly challenging task and this task is an important step in the development of a visual prosthesis. The receptive field structure of the retina layer is usually modeled as a 2D difference of Gaussian (DOG) filter profile. In the present study, as a different approach, a retina model including a 3D 2-stage DOG filter (3D-ADOG) that has an adaptively changing bandwidth with respect to the local image statistic is developed. Using this modeling, the adaptive image processing of the retina can be realized. The contribution of the developed model in terms of the image quality is evaluated via simulation studies using test images. The first simulation results, including only the spike count-based reconstruction for a test video sequence, were previously published. In this study, in addition to the spike count-based reconstruction, the interspike interval measure is also used in the simulation study. The reconstruction results are compared using the statistical parameters of the mean squared error (MSE), universal quality index (UQI), and histogram similarity ratio (HSR), which characterize the image likelihood. To evaluate the performance of the model versus time, time-dependent changes in the MSE, HSR, and UQI parameters are obtained and compared to the standard model. From these results, it is concluded that the 3D-ADOG filter-based retina model preserves the spatial details of the image and produces a larger number of different gray tone levels, which are important for the visual perception of an image, in comparison with the well-known classical DOG filter-based retina model. The retina implant systems based on this model can provide better visual perception for implant recipients.

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Adaptive artificial retina model to improve perception quality of retina implant recipients

Cited by 2 publications

References 18 publications

Spatio-Temporal Electrode Mapping and Local Interleaved Stimulation Method (STEMLIS) for Artificial Sight Systems

Spatio-Temporal Electrode Mapping and Local Interleaved Stimulation Method (STEMLIS) for Artificial Sight Systems

Spatiotemporal realization of an artificial retina model and performance evaluation through ISI- and spike count-based image reconstruction methods

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