Multispectral and autofluorescence RGB imaging for skin cancer diagnostics
This paper presents the results of statistical clinical data, combining two diagnostic methods. A combination of two skin imaging methods – diffuse reflectance and autofluorescence – has been applied for skin cancer diagnostics. Autofluorescence (AF) and multispectral diffuse reflectance images were acquired by custom made prototype with 405 nm, 526 nm, 663 nm and 964 nm LEDs and RGB CMOS camera. Parameter p’ was calculated from diffuse reflectance images under green, red and infrared illumination, AF intensity (I’) was calculated from AF images exited at 405nm wavelength. Obtained results show that criterion p` > 1 gives possibility to discriminate melanomas and different kind of keratosis…
Image quality enhancement for skin cancer optical diagnostics
The research presents image quality analysis and enhancement proposals in biophotonic area. The sources of image problems are reviewed and analyzed. The problems with most impact in biophotonic area are analyzed in terms of specific biophotonic task – skin cancer diagnostics. The results point out that main problem for skin cancer analysis is the skin illumination problems. Since it is often not possible to prevent illumination problems, the paper proposes image post processing algorithm – low frequency filtering. Practical results show diagnostic results improvement after using proposed filter. Along that, filter do not reduces diagnostic results’ quality for images without illumination de…
Quality enhancement of multispectral images for skin cancer optical diagnostics
Melanoma is the least common but deadliest skin cancer, accounting for only about 1% of all cases, but is the cause of the vast majority of skin cancer death. In some parts of the world, especially among western countries, melanoma is becoming more common every year. The detection of melanoma in early stage can be helpful to cure it. Unfortunately, long ques and high prices for dermatology service can result in the skin cancer diagnosis at its later stage, thus increasing the risk of mortality for the patient. It is important to provide a non-invasive optical device for primary care physicians to help diagnose different skin malformation based on obtained optical images. Such device will be…
A method for skin malformation classification by combining multispectral and skin autofluorescence imaging
As the incidence of skin cancer is still increasing worldwide, there is a high demand for early, non-invasive and inexpensive skin lesion diagnostics. In this article we describe and combine two skin imaging methods: skin autofluorescence (AF) and multispectral criterion p’. To develop this method, we used custom made prototype with 405 nm, 526 nm, 663 nm and 964 nm LED illuminations, perpendicular positioned linear polarizers, 515 nm filter and IDS camera. Our aim is to develop a skin lesion diagnostic device for primary care physicians who do not have experience in dermatology or skin oncology. In this study we included such common benign lesion groups as seborrheic keratosis, hyperkerato…
Semi-automated non-invasive diagnostics method for melanoma differentiation from nevi and pigmented basal cell carcinomas
The incidence of skin cancer is still increasing mostly in in industrialized countries with light- skinned people. Late tumour detection is the main reason of the high mortality associated with skin cancer. The accessibility of early diagnostics of skin cancer in Latvia is limited by several factors, such as high cost of dermatology services, long queues on state funded oncologist examinations, as well as inaccessibility of oncologists in the countryside regions - this is an actual clinical problem. The new strategies and guidelines for skin cancer early detection and post-surgical follow-up intend to realize the full body examination (FBE) by primary care physicians (general practitioners,…
Towards to deep neural network application with limited training data: synthesis of melanoma's diffuse reflectance spectral images
The goal of our study is to train artificial neural networks (ANN) using multispectral images of melanoma. Since the number of multispectral images of melanomas is limited, we offer to synthesize them from multispectral images of benign skin lesions. We used the previously created melanoma diagnostic criterion p'. This criterion is calculated from multispectral images of skin lesions captured under 526nm, 663nm, and 964nm LED illumination. We synthesize these three images from multispectral images of nevus so that the p' map matches the melanoma criteria (the values in the lesion area is >1, respectively). Demonstrated results show that by transforming multispectral images of benign nevus i…
Automated microorganisms activity detection on the early growth stage using artificial neural networks
The paper proposes an approach of a novel non-contact optical technique for early evaluation of microbial activity. Noncontact evaluation will exploit laser speckle contrast imaging technique in combination with artificial neural network (ANN) based image processing. Microbial activity evaluation process will comprise acquisition of time variable laser speckle patterns in given sample, ANN based image processing and visualization of obtained results. The proposed technology will measure microbial activity (like growth speed) and implement these results for counting live microbes. It is expected, that proposed technology will help to evaluate number of colony forming units (CFU) and return r…