The worldwide incidence of skin cancer has risen rapidly in the last decades, becoming one in three cancers nowadays. Currently, a person has a 4% chance of developing melanoma, the most aggressive form of skin cancer, which causes the greatest number of deaths. In the context of increasing incidence and mortality, skin cancer bears a heavy health and economic burden. Nevertheless, the 5-year survival rate for people with skin cancer significantly improves if the disease is detected and treated early. Accordingly, large research efforts have been devoted to achieve early detection and better understanding of the disease, with the aim of reversing the progressive trend of rising incidence and mortality, especially regarding melanoma. This paper reviews a variety of the optical modalities that have been used in the last years in order to improve non-invasive diagnosis of skin cancer, including confocal microscopy, multispectral imaging, three-dimensional topography, optical coherence tomography, polarimetry, self-mixing interferometry, and machine learning algorithms. The basics of each of these technologies together with the most relevant achievements obtained are described, as well as some of the obstacles still to be resolved and milestones to be met.

Background: We objectively assessed the optical quality and intraocular scattering by means of parameters provided by a clinical double‐pass system in healthy young subjects and thereby we obtained new reference data for clinical diagnosis. We calculated normal values of neural contrast sensitivity function (nCSF) from the measured modulation transfer function (MTF) and the contrast sensitivity function (CSF). Methods: Eligible subjects were healthy adults aged from 18 to 30 years with a logMAR visual acuity (VA) of 0.0 or better and normal values of CSF. Optical quality measurements for a 4.0 mm pupil were performed using the Optical Quality Analysis System (OQAS) based on the double‐pass technique. The following parameters were analysed: the modulation transfer function cutoff frequency (MTF_cutoff), the Strehl^2D ratio, the OQAS values (OV) at 100, 20 and nine per cent contrasts and the objective scatter index (OSI). Results: A total of 178 volunteers responded to the call, of whom 181 eyes were finally part of the study taking into account the criteria for inclusion. The values for the optical quality parameters were: 44.54 ± 7.14 cpd (MTF_cutoff), 0.27 ± 0.06 (Strehl^2D ratio), 1.48 ± 0.24 (OV_100%), 1.58 ± 0.32 (OV_20%), 1.64 ± 0.39 (OV_9%), and 0.38 ± 0.19 (OSI). The nCSF calculated was 1.76 ± 0.21 (3 cpd), 2.13 ± 0.23 (6 cpd), 2.01 ± 0.28 (12 cpd) and 1.86 ± 0.33 (18 cpd). Conclusion: The normal values provided can be a useful tool for discriminating healthy eyes from early abnormal ones in which the optical quality or sensory function is impaired.

With the goal of diagnosing skin cancer in an early and noninvasive way, an extended near infrared multispectral imaging system based on an InGaAs sensor with sensitivity from 995 nm to 1613 nm was built to evaluate deeper skin layers thanks to the higher penetration of photons at these wavelengths. The outcomes of this device were combined with those of a previously developed multispectral system that works in the visible and near infrared range (414 nm–995 nm). Both provide spectral and spatial information from skin lesions. A classification method to discriminate between melanomas and nevi was developed based on the analysis of first-order statistics descriptors, principal component analysis, and support vector machine tools. The system provided a sensitivity of 78.6% and a specificity of 84.6%, the latter one being improved with respect to that offered by silicon sensors.

Optical imaging systems for noninvasive ocular diagnosis remain crucial to assist ophthalmologists in their daily clinical practice. To promptly diagnose ocular and systemic diseases that manifest early in the retina,^{1 – 4} efforts have focused on the acquisition of good-quality fundus images. Commercial fundus cameras widely used in the clinical setting include digital cameras that produce color images, with only three spectral bands (R, G, and B). As a result, some retinal structures and substances with different spectral signatures associated with specific ocular diseases^5,6 may go undetected due to metamerism or limited spectral range. The capability of identifying these spectral absorption properties in-vivo is key to clinical diagnosis and treatment. Multispectral imaging (MSI) technology, which increases the amount of extractable spectral information from biological tissues using more than three spectral bands, has been used in the last few years to advance the diagnosis of many diseases.^{7 – 10} Newly developed fundus cameras that include MSI hold great promise for the analysis of the retina, since they combine the usefulness of spectroscopy with imaging, thus providing both spectral and spatial information of retinal landmarks. For instance, they can spotlight vascular occlusions, vein hemorrhages, drusen, and exudates, and also build oxygenation maps of the retinal vasculature, contributing in this way to the early diagnosis and treatment of conditions such as age-related macular degeneration (AMD) and diabetic retinopathy.^{11 – 16}

We examined the spectral reflectance of fundus structures in the visible and near-infrared (400–1300 nm) range for contributing to the medical diagnosis of fundus diseases. Spectral images of healthy eye fundus and other ocular diseases were acquired using a novel multispectral fundus camera. Reflectance metrics were computed based on contrast to analyze the spectral features. Significant differences were observed among the structures in healthy and diseased eye fundus. Specifically, near-infrared analysis allows imaging of deeper layers, such as the choroid, which, to date, has not been retrieved using traditional color fundus cameras. Pathological structures, which were hardly observable in color fundus images owing to metamerism, were also revealed by the developed multispectral fundus camera.

The effective and non-invasive diagnosis of skin cancer is a hot topic, since biopsy is a costly and time-consuming surgical procedure. As skin relief is an important biophysical feature that can be difficult to perceive with the naked eye and by touch, we developed a novel 3D imaging scanner based on fringe projection to obtain morphological parameters of skin lesions related to perimeter, area and volume with micrometric precision. We measured 608 samples and significant morphological differences were found between melanomas and nevi (p<0.001). The capacity of the 3D scanner to distinguish these lesions was supported by a supervised machine learning algorithm resulting in 80.0% sensitivity and 76.7% specificity.