0000000000033795

AUTHOR

Katrina Bolochko

0000-0003-0729-8009

showing 7 related works from this author

Multispectral and autofluorescence RGB imaging for skin cancer diagnostics

2019

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…

CMOS sensorMaterials scienceKeratosisbusiness.industryMultispectral imagemedicine.diseaselaw.inventionAutofluorescenceWavelengthOpticslawmedicineRGB color modelDiffuse reflectionbusinessLight-emitting diodeSaratov Fall Meeting 2018: Optical and Nano-Technologies for Biology and Medicine
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Image quality enhancement for skin cancer optical diagnostics

2017

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…

Image qualityComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFilter (signal processing)medicine.diseaseImage (mathematics)BiophotonicsOptical diagnosticsImage quality analysismedicinePoint (geometry)Computer visionArtificial intelligenceSkin cancerbusinessBiophotonics—Riga 2017
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Quality enhancement of multispectral images for skin cancer optical diagnostics

2018

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…

0301 basic medicineImage qualityComputer sciencebusiness.industrymedia_common.quotation_subjectMultispectral imagemedicine.disease01 natural sciencesField (computer science)Quality enhancement010309 opticsImage stabilization03 medical and health sciences030104 developmental biology0103 physical sciencesmedicineComputer visionQuality (business)Artificial intelligenceSkin cancerImage sensorbusinessmedia_commonOptics, Photonics, and Digital Technologies for Imaging Applications V
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A method for skin malformation classification by combining multispectral and skin autofluorescence imaging

2018

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…

Seborrheic keratosismedicine.medical_specialtyintegumentary systembusiness.industryMelanomaHyperkeratosisPrimary careBenign lesionSkin autofluorescencemedicine.diseaseDermatologymedicineBasal cell carcinomaSkin cancerbusinessBiophotonics: Photonic Solutions for Better Health Care VI
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Semi-automated non-invasive diagnostics method for melanoma differentiation from nevi and pigmented basal cell carcinomas

2017

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,…

medicine.medical_specialtyPigmented basal cell carcinomaSkin cancer early detectionintegumentary systembusiness.industryMelanomaNon invasivePrimary caremedicine.diseaseDermatologyTUMOUR DETECTIONmedicineBasal cellSkin cancerbusinessBiophotonics—Riga 2017
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Towards to deep neural network application with limited training data: synthesis of melanoma's diffuse reflectance spectral images

2019

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…

Training setLed illuminationArtificial neural networkbusiness.industryComputer scienceMelanomaMultispectral imagePattern recognitionmedicine.diseasemedicineNevusBenign nevusArtificial intelligenceSkin cancerbusinessDiffuse Optical Spectroscopy and Imaging VII
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Automated microorganisms activity detection on the early growth stage using artificial neural networks

2019

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…

Artificial neural networkComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProcess (computing)Pattern recognitionImage processingVisualizationSpeckle patternEnumerationSpeckle imagingStage (hydrology)Artificial intelligencebusinessNovel Biophotonics Techniques and Applications V
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