Automatically Enhanced OCT Scans of the Retina: A proof of concept study.

In this work we evaluated a postprocessing, customized automatic retinal OCT B-scan enhancement software for noise reduction, contrast enhancement and improved depth quality applicable to Heidelberg Engineering Spectralis OCT devices. A trained deep neural network was used to process images from an OCT dataset with ground truth biomarker gradings. Performance was assessed by the evaluation of two expert graders who evaluated image quality for B-scan with a clear preference for enhanced over original images. Objective measures such as SNR and noise estimation showed a significant improvement in quality. Presence grading of seven biomarkers IRF, SRF, ERM, Drusen, RPD, GA and iRORA resulted in similar intergrader agreement. Intergrader agreement was also compared with improvement in IRF and RPD, and disagreement in high variance biomarkers such as GA and iRORA.

Measuring the performance of visual to auditory information conversion.

BACKGROUND: Visual to auditory conversion systems have been in existence for several decades. Besides being among the front runners in providing visual capabilities to blind users, the auditory cues generated from image sonification systems are still easier to learn and adapt to compared to other similar techniques. Other advantages include low cost, easy customizability, and universality. However, every system developed so far has its own set of strengths and weaknesses. In order to improve these systems further, we propose an automated and quantitative method to measure the performance of such systems. With these quantitative measurements, it is possible to gauge the relative strengths and weaknesses of different systems and rank the systems accordingly. METHODOLOGY: Performance is measured by both the interpretability and also the information preservation of visual to auditory conversions. Interpretability is measured by computing the correlation of inter image distance (IID) and inter sound distance (ISD) whereas the information preservation is computed by applying Information Theory to measure the entropy of both visual and corresponding auditory signals. These measurements provide a basis and some insights on how the systems work. CONCLUSIONS: With an automated interpretability measure as a standard, more image sonification systems can be developed, compared, and then improved. Even though the measure does not test systems as thoroughly as carefully designed psychological experiments, a quantitative measurement like the one proposed here can compare systems to a certain degree without incurring much cost. Underlying this research is the hope that a major breakthrough in image sonification systems will allow blind users to cost effectively regain enough visual functions to allow them to lead secure and productive lives.