Search results for "Biomedical optical imaging"

showing 4 items of 4 documents

First Retrievals of ASCAT-IB VOD (Vegetation Optical Depth) at Global Scale

2021

Global and long-term vegetation optical depth (VOD) dataset are very useful to monitor the dynamics of the vegetation features, climate and environmental changes. In this study, the radar-based global ASCAT (Advanced SCATterometer) IB (INRAE-BORDEAUX) VOD was retrieved using a model which was recently calibrated over Africa. In order to assess the performance of IB VOD, the Saatchi biomass and three other VOD datasets (ASCAT V16, AMSR2 LPRM V5 and VODCA LPRM V6) derived from C-band observations were used in the comparison. The preliminary results show that IB VOD has a promising ability to predict biomass $(\mathrm{R}=0.74,\ \text{RMSE} =44.82\ \text{Mg}\ \text{ha}^{-1})$ , which is better …

Vegetation optical depth010504 meteorology & atmospheric sciencesvegetation mapping0211 other engineering and technologiesScale (descriptive set theory)02 engineering and technology01 natural sciencesCombinatoricsremote sensingvegetationoptical sensorC-bandComputingMilieux_MISCELLANEOUSattenuation021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsprediction algorithmbiomassOrder (ring theory)15. Life on landPrediction algorithmsASCAT13. Climate action[SDE]Environmental SciencesVegetation optical DepthScatterometerBiomedical optical imagingRadar Measurement
researchProduct

Differentiating Malignant from Benign Pigmented or Non-Pigmented Skin Tumours—A Pilot Study on 3D Hyperspectral Imaging of Complex Skin Surfaces and …

2022

Several optical imaging techniques have been developed to ease the burden of skin cancer disease on our health care system. Hyperspectral images can be used to identify biological tissues by their diffuse reflected spectra. In this second part of a three-phase pilot study, we used a novel hand-held SICSURFIS Spectral Imager with an adaptable field of view and target-wise selectable wavelength channels to provide detailed spectral and spatial data for lesions on complex surfaces. The hyperspectral images (33 wavelengths, 477–891 nm) provided photometric data through individually controlled illumination modules, enabling convolutional networks to utilise spectral, spatial, and skin-surface mo…

OPTICAL COHERENCE TOMOGRAPHYskin cancerhyperspectral imagingskin imagingphotometric stereoMELANOMAGeneral Medicineneuroverkotdiagnostiikkabiomedical optical imagingnon-invasive imagingDIAGNOSISCANCERoptical modellingkarsinoomatCLASSIFICATIONihosyöpäkoneoppiminenSDG 3 - Good Health and Well-beingbiomedical optical imaging; convolutional neural networks; hyperspectral imaging; non-invasive imaging; optical modelling; photometric stereo; skin cancer; skin imaging3121 General medicine internal medicine and other clinical medicineconvolutional neural networks/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingmelanoomahyperspektrikuvantaminen
researchProduct

Melanoma-Nevus Discrimination Based on Image Statistics in Few Spectral Channels

2016

The purpose of this paper is to offer a method for discrimination of cutaneous melanoma from benign nevus, founded on analysis of skin lesion image. At the core of method is calculation of mean and standard deviation of pixel optical density values for a few narrow spectral bands. Calculated values are compared with discriminating thresholds derived from a set of images of benign nevi and melanomas with known diagnosis. Classification is done applying weighted majority rule to results of thresholding. Verification against the available multispectral images of 32 melanomas and 94 benign nevi has shown that the method using three spectral bands provided zero false negative and four false posi…

0301 basic medicineNevi and melanomasContextual image classificationImage classificationmelanoma detection.Multispectral imageSpectral bandsbiomedical optical imagingmedicine.disease01 natural sciencesThresholdingStandard deviation010104 statistics & probability03 medical and health sciences030104 developmental biologyCutaneous melanomaStatisticsmultispectral imagingmedicineNevus0101 mathematicsElectrical and Electronic EngineeringMathematicsElektronika ir Elektrotechnika
researchProduct

Automated approach for indirect immunofluorescence images classification based on unsupervised clustering method

2018

Autoimmune diseases (ADs) are a collection of many complex disorders of unknown aetiology resulting in immune responses to self-antigens and are thought to result from interactions between genetic and environmental factors. ADs collectively are amongst the most prevalent diseases in the U.S., affecting at least 7% of the population. The diagnosis of ADs is very complex, the standard screening methods provides seeking and recognizing of Antinuclear Antibodies (ANA) by Indirect ImmunoFluorescence (IIF) based on HEp-2 cells. In this paper an automatic system able to identify and classify the Centromere pattern is presented. The method is based on the grouping of centromeres present on the cell…

medical disorderComputer sciencePopulationFeature extraction02 engineering and technologybiomedical optical imagingmedical image processing030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineImage textureblood0202 electrical engineering electronic engineering information engineeringSegmentationimage texturecellular biophysicsCluster analysiseducationimage segmentationdiseaseeducation.field_of_studyIndirect immunofluorescenceContextual image classificationbusiness.industryfeature extractionPattern recognitionImage segmentationSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)020201 artificial intelligence & image processingfluorescenceComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareimage classificationIET Computer Vision
researchProduct