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This study proposes the combination of multispectral and 3D imaging sensors to improve the detection of skin cancer. [...]

International audience; This article proposes a multispectral system that uses the analysis of the spatial distribution of color and spectral features to improve the detection of skin cancer lesions, specifically melanomas and basal cell carcinomas. The system consists of a digital camera and light-emitting diodes of eight different wavelengths (414 to 995 nm). The parameters based on spectral features of the lesions such as reflectance and color, as well as others empirically computed using reflectance values, were calculated pixel-by-pixel from the images obtained. Statistical descriptors were calculated for every segmented lesion [mean ( x ˜ ), standard deviation ( σ ), minimum, and maximum]; descriptors based on the first-order statistics of the histogram [entropy ( E p ), energy ( E n ), and third central moment ( μ 3 )] were also obtained. The study analyzed 429 pigmented and nonpigmented lesions: 290 nevi and 139 malignant (95 melanomas and 44 basal cell carcinomas), which were split into training and validation sets. Fifteen parameters were found to provide the best sensitivity (87.2% melanomas and 100% basal cell carcinomas) and specificity (54.5%). The results suggest that the extraction of textural information can contribute to the diagnosis of melanomas and basal cell carcinomas as a supporting tool to dermoscopy and confocal microscopy.

This study analyzes the repeatability, reproducibility and accuracy of a new hyperspectral system based on a pushbroom sensor as a means of measuring spectral features and color of materials and objects. The hyperspectral system consisted of a CCD camera, a spectrograph and an objective lens. An additional linear moving system allowed the mechanical scanning of the complete scene. A uniform overhead luminaire with daylight configuration was used to irradiate the scene using d:45 geometry. We followed the guidelines of the ASTM E2214-08 Standard Practice for Specifying and Verifying the Performance of Color-Measuring Instruments that define the standards and latest multidimensional procedures. The results obtained are analyzed in-depth and compared to those recently reported by other authors for spectrophotometers and multispectral systems. It can be concluded that hyperspectral systems are reliable and can be used in the industry to perform spectral and color readings with a high spatial resolution. Contract grant sponsor: Spanish Ministry of Education and Science; contract grant numbers: DPI2008-06455-C02-01, DPI DPI2011-30090-C02-01; Contract grant sponsor: European Union.

This erratum corrects the error of an omitted author in doi: http://dx.doi.org/10.1117/1.JBO.22.6.065006

The process of separating small vertebrate fossils from sediment is a monotonous exercise, usually carried out manually and mainly based on morphological features. The large amount of time and personnel required results in the high economic costs associated with this antiquated technique. In this study we test the potential of colour and multispectral imaging for the detection of small vertebrate fossils to facilitate their separation from sediment. This technique is based on the analysis of the spectral and fluorescence characteristics of fossils. Specifically, a multispectral system with a charge-coupled device (CCD) camera attached to a liquid crystal tunable filter and a digital colour camera was used in combination with daylight and ultraviolet light sources. The results show that the reflectance of bones, teeth and sediment are usually different at longer wavelengths, and that fluorescence rates also differ in the bluegreen region. Unfortunately, samples from different paleontological sites present different patterns, hindering the standardization of a method that discriminates microfossils from sediments. However, the combination of colour and multispectral imaging systems with recent advances in laser-stimulated fluorescence in fossils could constitute an optimal solution for an efficient sorting process of small vertebrate remains within geological samples.

We present a handheld scanning system for measuring in-vivo the 3D topography of the human skin surface. The system has been envisaged for analyzing the 3D shape of skin cancer lesions, providing a more precise characterization of the lesions compared with the conventional examination done by using the naked eye and dermoscopy methods. The 3D scanning system is composed of cost-effective and commercially available components, including two monochrome cameras placed in a stereo configuration, a color camera, and a compact projector unit. The 3D measuring principle is based on the technique of stereovision combined with the projection of structured light patterns. A first scanning prototype has been recently developed for imaging skin surface areas of 19 x 14 mm 2 . A graphical user interface (GUI) has been also implemented to operate with the prototype. Preliminary experimental results showing the performance of this initial prototype for imaging different skin surface zones are also presented.

The effective and non-invasive diagnosis of skin cancer is a hot topic in biophotonics since the current gold standard, biopsy followed by histological examination, is a slow and costly procedure for the healthcare system. Therefore, authors have put their efforts in characterizing skin cancer quantitatively through optical and photonic techniques such as 3D topography and multispectral imaging. Skin relief is an important biophysical feature that can be difficult to appreciate by touch, but can be precisely characterized with 3D imaging techniques, such as fringe projection. Color and spectral features given by skin chromophores, which are routinely analyzed by the naked eye and through dermoscopy, can also be quantified by means of multispectral imaging systems. In this study, the outcomes of these two imaging modalities were combined in a machine learning process to enhance classification of melanomas and nevi obtained from the two systems when operating isolately. The results suggest that the combination of 3D and multispectral data is relevant for the medical diagnosis of skin cancer.

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.

The effective and non-invasive diagnosis of skin cancer is a hot topic in biophotonics since the current gold standard, a biopsy, is slow and costly. Non-invasive optical techniques such as polarization and multispectral imaging have arisen as powerful tools to overcome these constraints. The combination of these techniques provides a comprehensive characterization of skin chromophores including polarization, color and spectral features. Hence, in this work we propose a polarized multispectral imaging device that works from 414 nm to 995 nm and at 0º, 45º and 90º polarization configurations. Preliminary results performed over 20 nevi and 20 melanoma found statistically significant descriptors (p