Fundamental challenge of imaging through a scattering media has been resolved by various approaches in the past two decades. Optical wavefront shaping technique is one such method in which one shapes the wavefront of light entering a scattering media using a wavefront shaper such that it cancels the scattering effect. It has been the most effective technique in focusing light inside a scattering media. Unfortunately, most of these techniques require direct access to the scattering medium or need to know the scattering properties of the medium beforehand. Through the novel scheme presented on this paper, both the illumination module and the detection are on the same side of the inspected object and the imaging process is a real time fast converging operation. We model the scattering medium being a biological tissue as a matrix having mathematical properties matched to the physical and biological aspects of the sample. In our adaptive optics scheme, we aim to estimate the scattering function and thus to encode the intensity of the illuminating laser light source using DMD (Digital Micromirror Device) with an inverse scattering function of the scattering medium, such that after passing its scattering function a focused beam is obtained. We optimize the pattern to be displayed on the DMD using Particle Swarm Algorithm (PSO) which eventually help in retrieving a 1D object hidden behind the media.

This paper aims to present initial proof of concept of a non-invasive early diagnostic tool for Alzheimer disease (AD). The approach is based on the identification using Raman spectroscopy and machine learning algorithms of two proteins that are linked with AD and exist in the cerebrospinal fluid (CSF). As demonstrated in previous studies, the concentration of the proteins amyloid-β and tau may indicate the existence of AD. The proteins’ concentration in the CSF signifies the condition of AD. The current study can contribute to the existing body of knowledge by enabling the development of a non-invasive diagnostic tool that may help with early diagnosis of AD.

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An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Superoscillation is a technique that is used to produce a spot of light (known as 'hotspot') which is smaller than the conventional diffraction limit of a lens and even smaller than the optical wavelength. Over the past few years, several techniques have been realized for the generation of the superoscillatory hotspot. In this article, for the first time to the best of our knowledge, we propose a novel and a more efficient technique for producing superoscillation in microscopic imaging by shaping the coherent transfer function (CTF) of a lens via virtual Fourier filtering followed by a phase retrieval algorithm. We design and realize a phase mask which when placed at the pupil plane of a diffractionlimited lens produces a superoscillatory hotspot with sidelobes properly matched to the field of view (FOV) required in microscopic imaging applications, i.e. hotspot always coexists with huge intense rings known as 'sidebands' close to it and hence limiting the FOV. our technique is also capable of extending the FOV with minimal loss in resolution of the hotspot generated and considerable ratio between the intensity of the hotspot to that of the side lobes while optimizing the obtainable FOV to the requirement of microscopy.