Department of Biomedical Engineering, Helwan University, Helwan, Egypt.
School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
J Healthc Eng. 2018 Apr 18;2018:3493826. doi: 10.1155/2018/3493826. eCollection 2018.
Retinal prosthesis is steadily improving as a clinical treatment for blindness caused by retinitis pigmentosa. However, despite the continued exciting progress, the level of visual return is still very poor. It is also unlikely that those utilising these devices will stop being legally blind in the near future. Therefore, it is important to develop methods to maximise the transfer of useful information extracted from the visual scene. Such an approach can be achieved by digitally suppressing less important visual features and textures within the scene. The result can be interpreted as a cartoon-like image of the scene. Furthermore, utilising extravisual wavelengths such as infrared can be useful in the decision process to determine the optimal information to present. In this paper, we, therefore, present a processing methodology that utilises information extracted from the infrared spectrum to assist in the preprocessing of the visual image prior to conversion to retinal information. We demonstrate how this allows for enhanced recognition and how it could be implemented for optogenetic forms of retinal prosthesis. The new approach has been quantitatively evaluated on volunteers showing 112% enhancement in recognizing objects over normal approaches.
视网膜假体作为治疗色素性视网膜炎引起的失明的一种临床治疗方法，正在稳步改进。然而，尽管不断取得令人兴奋的进展，但视觉恢复的水平仍然非常低。在不久的将来，那些使用这些设备的人也不太可能不再是法定盲人。因此，开发最大限度地从视觉场景中提取有用信息的方法非常重要。通过数字化抑制场景中不太重要的视觉特征和纹理，可以实现这种方法。结果可以解释为场景的卡通图像。此外，利用额外的视觉波长，如红外线，在确定要呈现的最佳信息的决策过程中可能很有用。因此，在本文中，我们提出了一种处理方法，该方法利用从红外光谱中提取的信息来辅助视觉图像的预处理，然后再将其转换为视网膜信息。我们展示了这如何允许增强识别，以及它如何可以为光遗传学形式的视网膜假体实现。该新方法已经在志愿者身上进行了定量评估，结果显示，在识别物体方面，与正常方法相比，增强了 112%。
