Analysis of peripheral arterial disease (PAD) patients by laser speckle measurement techniques.

Diabetic foot is a well-known problem among patients suffering from peripheral arterial diseases (PAD). This article presents an optical sensor for contactless measurement of the anatomical site based on laser speckle techniques. The sensor illuminates the inspected tissue and analyzes the captured back-reflected light from the time-changing speckle patterns. An occlusion test was implemented to provide a statistical parameter to differentiate between a low perfused and a healthy foot. A clinical study of 15 subjects was conducted. The video was analyzed by two methods: dynamic laser speckle (DLS) and laser speckle contrast analysis (LASCA). Data analysis included several classification models, where the KNN model exhibited maximum performance. These findings suggest that a simple and inexpensive system for PAD monitoring can be designed for home use and/or in community clinics.

Non-contact photoacoustic imaging using laser speckle contrast analysis.

A novel method for non-contact and continuous detection of photoacoustic signals is presented and experimentally demonstrated. The approach is based on analysis of the contrast of time-varying speckle patterns, and suggests a more robust alternative in respect to interferometric and refractometric available solutions.

Autoencoder based blind source separation for photoacoustic resolution enhancement.

Photoacoustics is a promising technique for in-depth imaging of biological tissues. However, the lateral resolution of photoacoustic imaging is limited by size of the optical excitation spot, and therefore by light diffraction and scattering. Several super-resolution approaches, among which methods based on localization of labels and particles, have been suggested, presenting promising but limited solutions. This work demonstrates a novel concept for extended-resolution imaging based on separation and localization of multiple sub-pixel absorbers, each characterized by a distinct acoustic response. Sparse autoencoder algorithm is used to blindly decompose the acoustic signal into its various sources and resolve sub-pixel features. This method can be used independently or as a combination with other super-resolution techniques to gain further resolution enhancement and may also be extended to other imaging schemes. In this paper, the general idea is presented in details and experimentally demonstrated.