Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imaging.

BACKGROUND AND OBJECTIVES: Advanced artificial intelligence and machine learning have great potential to redefine how skin lesions are detected, mapped, tracked and documented. Here, we propose a 3D whole-body imaging system known as 3DSkin-mapper to enable automated detection, evaluation and mapping of skin lesions. METHODS: A modular camera rig arranged in a cylindrical configuration was designed to automatically capture images of the entire skin surface of a subject synchronously from multiple angles. Based on the images, we developed algorithms for 3D model reconstruction, data processing and skin lesion detection and tracking based on deep convolutional neural networks. We also introduced a customised, user-friendly, and adaptable interface that enables individuals to interactively visualise, manipulate, and annotate the images. The interface includes built-in features such as mapping 2D skin lesions onto the corresponding 3D model. RESULTS: The proposed system is developed for skin lesion screening, the focus of this paper is to introduce the system instead of clinical study. Using synthetic and real images we demonstrate the effectiveness of the proposed system by providing multiple views of a target skin lesion, enabling further 3D geometry analysis and longitudinal tracking. Skin lesions are identified as outliers which deserve more attention from a skin cancer physician. Our detector leverages expert annotated labels to learn representations of skin lesions, while capturing the effects of anatomical variability. It takes only a few seconds to capture the entire skin surface, and about half an hour to process and analyse the images. CONCLUSIONS: Our experiments show that the proposed system allows fast and easy whole body 3D imaging. It can be used by dermatological clinics to conduct skin screening, detect and track skin lesions over time, identify suspicious lesions, and document pigmented lesions. The system can potentially save clinicians time and effort significantly. The 3D imaging and analysis has the potential to change the paradigm of whole body photography with many applications in skin diseases, including inflammatory and pigmentary disorders. With reduced time requirements for recording and documenting high-quality skin information, doctors could spend more time providing better-quality treatment based on more detailed and accurate information.

Psychophysical Evaluation of a Tactile Display Based on Coin Motors.

Tactile vision substitution devices present visual images as tactile representations on the skin. In this study we have tested the performance of a prototype 96-tactor vibrotactile using a subset of 64 tactors. We have determined the tactile spatial acuity and intensity discrimination in 14 naïve subjects. Spatial acuity was determined using a grating acuity task. Subjects could successfully identify the orientation of horizontal and vertical gratings with an average psychophysical threshold of 120 mm. When diagonal gratings were included in the analysis, the median performance dropped below psychophysical threshold, but was still significantly above chance at gratings of 142 mm wide. Intensity discrimination yielded an average Weber fraction of 0.44, corresponding to 13 discernable "gray levels" in the available dynamic range. Interleaved stimulation of the motors did not significantly affect spatial acuity or intensity discrimination.

Vision function testing for a suprachoroidal retinal prosthesis: effects of image filtering.

OBJECTIVE: One strategy to improve the effectiveness of prosthetic vision devices is to process incoming images to ensure that key information can be perceived by the user. This paper presents the first comprehensive results of vision function testing for a suprachoroidal retinal prosthetic device utilizing of 20 stimulating electrodes. Further, we investigate whether using image filtering can improve results on a light localization task for implanted participants compared to minimal vision processing. No controlled implanted participant studies have yet investigated whether vision processing methods that are not task-specific can lead to improved results. APPROACH: Three participants with profound vision loss from retinitis pigmentosa were implanted with a suprachoroidal retinal prosthesis. All three completed multiple trials of a light localization test, and one participant completed multiple trials of acuity tests. The visual representations used were: Lanczos2 (a high quality Nyquist bandlimited downsampling filter); minimal vision processing (MVP); wide view regional averaging filtering (WV); scrambled; and, system off. MAIN RESULTS: Using Lanczos2, all three participants successfully completed a light localization task and obtained a significantly higher percentage of correct responses than using MVP ([Formula: see text]) or with system off ([Formula: see text]). Further, in a preliminary result using Lanczos2, one participant successfully completed grating acuity and Landolt C tasks, and showed significantly better performance ([Formula: see text]) compared to WV, scrambled and system off on the grating acuity task. SIGNIFICANCE: Participants successfully completed vision tasks using a 20 electrode suprachoroidal retinal prosthesis. Vision processing with a Nyquist bandlimited image filter has shown an advantage for a light localization task. This result suggests that this and targeted, more advanced vision processing schemes may become important components of retinal prostheses to enhance performance. ClinicalTrials.gov Identifier: NCT01503576.

A salient information processing system for bionic eye with application to obstacle avoidance.

In this paper we present a visual processing system for bionic eye with a focus on obstacle avoidance. Bionic eye aims at restoring the sense of vision to people living with blindness and low vision. However, current hardware implant technology limits the image resolution of the electrical stimulation device to be very low (e.g., 100 electrode arrays, which is approx. 12 × 9 pixels). Therefore, we need a visual processing unit that extracts salient information in an unknown environment for assisting patients in daily tasks such as obstacle avoidance. We implemented a fully portable system that includes a camera for capturing videos, a laptop for processing information using a state-of-the-art saliency detection algorithm, and a head-mounted display to visualize results. The experimental environment consists of a number of objects, such as shoes, boxes, and foot stands, on a textured ground plane. Our results show that the system efficiently processes the images, effectively identifies the obstacles, and eventually provides useful information for obstacle avoidance.