Ординатура / Офтальмология / Английские материалы / Artificial Sight Basic Research, Biomedical Engineering, and Clinical Advances_Humayun, Weiland, Chader_2007

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y

There are several well-known gradient filters. In our experiment we use the Sobel gradients, which are obtained by convolving the image with the following kernels:

Edge Following

If an object in an image has a discrete edge all around it, and also a beginning position on the edge has been found, it is possible to follow the edge of the object and back to the beginning position. Edge following is a very useful operation, particularly as a stepping stone to making decisions by discovering region positions in images. This is effectively the dual of segmentation by region detection.

Edge detectors yield pixels in an image lying on edges. The next step is to collect these pixels together into a set of edges. Thus, the whole object can be present simply by a few edges around it.

Binary Morphological Operations

Binary morphological operations are defined on bi-level images, which consist of either black or white pixels only. Dilation and erosion are popular binary morphological operations. If dilation can be said to add pixels to an object or to make it bigger, then erosion will make an object smaller.

Erosion can be used to eliminate unwanted white noise pixels from another black area. The only condition in which a white pixel will remain white in the output image is that all of its neighbors are white. The effect of erosion on a binary image is to diminish the edges of a white area of pixels and make the object look smaller than ever. The same rules applied to erosion can also be applied to dilation. But the logic must be inverted – using the NAND rather than the AND logical operation. Compared to erosion, dilation will allow a black pixel to remain black only when all of its neighbors are black. This operator is useful for removing isolated black pixels from an image.

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Figure 10.13. The process of visual information extraction: (a) original image, (b) the image after edge following, (c) the image after edge detection, and (d) the image after dilation based on edge image.

to implement other algorithms by our DSP image processing platform. Once more advanced algorithms are fulfilled, the basic function of visual information extraction of retina can be replaced by our optic nerve prosthesis.

Neural Electrical Stimulator

According to the experiment results of Claude Veraart et al., the stimulation based on optic nerve needs biphasic current pulses with variable amplitudes (from several microamperes up to several milliamperes), pulse duration (from several microseconds up to hundreds of microseconds) and pulse frequency. Then multiple biphasic current pulses make up one pulse train.

Figure 10.14. The visual information extraction by DSP: (a) original image captured by micro-camera, (b) the image after edge detection by DSP.

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a normally illuminated room condition is about 3 to 4 mm; we chose the dimension of the micro-camera as 5 mm long and 4 mm wide as demonstrated in Figure 10.16. The micro-lens should be of wide angle and short focal length, such that the visual field could be extended.

The necessary highest resolution of the CMOS could be calculated based on visual discrimination. For example, for a given focal length of 4 mm of the micro-lens, if the best discrimination ability was described with visual angle of 10 minutes of arc or more, the maximum single pixel should not be larger than 5 m. Much higher resolution could consume more power, hence more heat would be created, which was a considerable problem since it was to be implanted into the eye. In addition, more time was needed for the data processing which also should be taken into account with real time visual purpose.

Evaluation of the Micro-Camera in the Model Eye

In order to evaluate the imaging quality of the micro-camera in different environments, we put the micro-camera in the position of the crystalline lens of a model test eye (Figure 10.17). The model test eye was full of 0.9 % NaCl fluid when the pictures were to be taken in order to simulate the internal circumstance of the anterior chamber of the eye. The images were recorded with the target at different distances from the model test eye. It was demonstrated that the images became only a little blurred when recorded with the micro-camera in 0.9 % NaCl fluid (Figure 10.18). It also could be seen that the depth of field was large enough for the visual prosthesis to “see” clearly in the near and middle distance. In addition, it might have enough resolution for the image information extraction to correctly stimulate the optic nerve or neurons.

Figure 10.16. The implantable micro-camera including micro-lens, CMOS and cable (Top). The sketches of the implantable micro-camera (Bottom).

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biocompatible material. However, these are very preliminary results. Further studies need to be carried out to implant the micro-camera into a cat’s eye to evaluate the long-term biocompatibility and imaging function.

Conclusion

A type of visual prosthesis with stimulating electrode penetrating into optic nerve is introduced in this chapter. The feasibility of this visual prosthesis has been validated using some animal experiments. Many more animal experiments will be carried out to find out the rules of visual perception elicited by electrical stimulation in our project. To some degree, the hardware design of visual prosthesis depends much on the development of MOEMS technology. But a number of effective image-processing strategies can be explored and evaluated to enhance the performance of visual prosthesis and even decrease the difficulty of complex hardware design. In this chapter, we presented some tests of image-processing strategies by computer simulation and DSP implementation in real time. A high precision neural stimulator is also under study. An implantable CMOS microcamera with special design is also evaluated. Although much more tests for its long-term biocompatibility must be carried out, the preliminary results showed that the micro-camera was suitable for our visual prosthesis with minimal loss of image quality in the simulation physiological circumstance.

References

1.Brindley GS, Lewin WS, The sensations produced by electrical stimulation of the visual cortex, J. Physiol. (Lond), 1968, 196:479–493.

2.Dobelle WH, Mladejowsky MG, Artificial vision for the blind: electrical stimulation of visual cortex offers hope for a functional prosthesis, Science, 1974, 183:40–44.

3.Schmidt EM, Bak MJ, Hambrecht FT, Kufta CV, O’Rourke NA, Vallabhanath P, Feasibility of a visual prosthesis for the blind based on intracortical microstimulation of the visual cortex, Brain, 1996, 119:507–522.

4.Zrenner E, Miliczek KD, Gabel VP, Graf HG, Guenther E, Haemmerle H, Hoefflinger B, Kohler K, Nisch W, Schubert M, Stett A, Weiss S, The development of subretinal micro-photodiodes for replacement of degenerated photoreceptors, Ophthalmic Res., 1997, 29:269–280.

5.Humayun MS, de Juan Jr E, Weiland JD, Dagnelie G, Katona S, Greenberg R, Suzuki S, Pattern electrical stimulation of the human retina, Vision Res., 1999, 39:2569–2576.

6.Chow AY, Pardue MT, Chow VY, Peyman GA, Liang C, Perlman JI, Peachy NS, Implantation of silicon chip microphotodiode arrays into the cat subretinal space. IEEE Trans. Neural Sys. Rehabilitation Eng., 2001, 9:86–95.

7.Veraart C, Raftopoulos C, Mortimer JT, Delbeke J, Pins D, Michaux G, Vanlierde A, Parrini Sand Wanet-Defalque MC, Visual sensations produced by optic nerve stimulation using an implanted self-sizing spiral cuff electrode, Brain Research, 1998, 813:181–186.

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