Search results for "Imaging data"

showing 7 items of 17 documents

Thermal structure of a hot non-flaring corona from Hinode/EIS

2014

In previous studies a very hot plasma component has been diagnosed in solar active regions through the images in three different narrow-band channels of SDO/AIA. This diagnostic from EUV imaging data has also been supported by the matching morphology of the emission in the hot Ca XVII line, as observed with Hinode/EIS. This evidence is debated because of unknown distribution of the emission measure along the line of sight. Here we investigate in detail the thermal distribution of one of such regions using EUV spectroscopic data. In an active region observed with SDO/AIA, Hinode/EIS and XRT, we select a subregion with a very hot plasma component and another cooler one for comparison. The ave…

PhysicsSun: corona Sun: UV radiation Sun: X-rays gamma rays techniques: spectroscopic techniques: imaging spectroscopyLine-of-sightSun: coronaExtreme ultraviolet lithographyTechniques: spectroscopicFOS: Physical sciencesAstronomy and AstrophysicsThermal distributionPlasmaAstrophysicsAstronomy and AstrophysicSun: UV radiationImaging dataCoronaSettore FIS/05 - Astronomia E AstrofisicaAstrophysics - Solar and Stellar AstrophysicsSun: X-rays gamma raySpace and Planetary ScienceThermalTechniques: imaging spectroscopySolar and Stellar Astrophysics (astro-ph.SR)Line (formation)Astronomy & Astrophysics
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Virtual Reality Based Simulators for Neurosurgeons - What We Have and What We Hope to Have in the Nearest Future

2018

High levels of manual skills, good visual-motor coordination, excel‐lent imagination and spatial awareness are the main factors determining the success of neurosurgeons. Proficiency in neurosurgical skills used to be acquired through hands-on training in cadaver labs and in real operating theatres under master neurosurgeon supervision. Most recently, virtual reality (VR) and augmented reality (AR) computer simulations have also been considered as tools for education in the neurosurgical training. The authors review existing solutions and present their own concept of a simulator which could become the useful tool for planning, simulation and training of a specific neurosurgical procedure usi…

Spatial contextual awarenessOperating theatresComputer scienceContext (language use)Medical trainingVirtual realityImaging dataField (computer science)Virtual realityNeurosurgical Procedure03 medical and health sciences0302 clinical medicineHuman–computer interaction030220 oncology & carcinogenesisAugmented realityNeurosurgical simulator030217 neurology & neurosurgery
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Cancer: Clinical Background and Key Challenges

2011

This chapter is aimed at a wide audience ranging from biologists to medical students and cancer specialists. It provides a comprehensive overview of systems approaches to the pathology and treatment of cancer. In particular, it addresses diagnosis and therapy by interconnecting various aspects of cancer at both the molecular and clinical level, and contrasts the unifying features of malignancies with the daunting diversity of cancer types, stages, and evolutionary processes during treatment. The importance is emphasized of both prevention and innovative treatments in reducing the cancer burden, and of early detection as the link between these two major areas. It sets the stage for analysis …

Systems medicinebusiness.industrySystems biologyEarly detectionMedicineResearch needsSystems approachesBioinformaticsbusinessData scienceGrading (tumors)Signalling pathwaysImaging data
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Filtering and emission area identification in the Time Resolved Imaging data

2012

Abstract Time Resolved Imaging (TRI) acquisitions allow precise timing analysis of emission spots. Up to date technologies deeply challenge their isolation by hiding the weak ones, under sizing or over sizing visually detectable emission spots and finally by jeopardizing timing resolution. We report on an algorithm based on 1 and 2D signal processing tools which automates the identification of emission sites and optimizes separation between noise and useful signal, even for weak spots surrounding strong emission areas. The application of the algorithm on several sets of data from different types of devices and their results are also discussed.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology01 natural sciencesImaging dataSignal[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringIsolation (database systems)[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing010302 applied physicsSignal processingNoise (signal processing)business.industryPhoto EmissionStatic timing analysisPattern recognitionSizingIdentification (information)IC Failure AnalysisImage Thresholding[ SPI.NANO ] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Applying fully tensorial ICA to fMRI data

2016

There are two aspects in functional magnetic resonance imaging (fMRI) data that make them awkward to analyse with traditional multivariate methods - high order and high dimension. The first of these refers to the tensorial nature of observations as array-valued elements instead of vectors. Although this can be circumvented by vectorizing the array, doing so simultaneously loses all the structural information in the original observations. The second aspect refers to the high dimensionality along each dimension making the concept of dimension reduction a valuable tool in the processing of fMRI data. Different methods of tensor dimension reduction are currently gaining popUlarity in literature…

computer.software_genre01 natural sciencesTask (project management)010104 statistics & probability03 medical and health sciences0302 clinical medicineDimension (vector space)medicinePreprocessorTensor0101 mathematicsMathematicsta112medicine.diagnostic_testbusiness.industryDimensionality reductionfMRIPattern recognitionIndependent component analysisdataPrincipal component analysisData miningArtificial intelligencefunctional magnetic resonance imaging databusinessFunctional magnetic resonance imagingcomputer030217 neurology & neurosurgery2016 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)
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Evaluation of Skin Melanoma in Spectral Range 450-950 nm Using Principal Component Analysis

2013

Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450-950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.

medicine.medical_specialtyMaterials scienceintegumentary systemWavelength rangebusiness.industryMelanomamedicine.diseaseImaging dataSpectral imagingOpticsNuclear magnetic resonancePrincipal component analysisPigmented NevusmedicineSkin melanomabusinessneoplasms
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Can Early Postoperative O-(2-18FFluoroethyl)-l-Tyrosine Positron Emission Tomography After Resection of Glioblastoma Predict the Location of Later Tu…

2019

Objective Glioblastoma inevitably recurs despite aggressive therapy. Therefore, it would be helpful to predict the location of tumor recurrence from postoperative imaging to customize further treatment. O-(2-18Ffluoroethyl)- l -tyrosine (FET) positron emission tomography (PET) might be a helpful technique, because tumor tissue can be differentiated from normal brain tissue with high specificity. Methods Thirty-two consecutive patients with perioperative and follow-up imaging data available were included. On postoperative FET-PET, the tumor/normal brain (TTB) ratio around the resection cavity borders was measured. Increased TTB ratios were recorded and anatomically correlated with the site o…

medicine.medical_specialtymedicine.diagnostic_testbusiness.industrymedicine.medical_treatmentMagnetic resonance imagingPerioperativemedicine.diseaseImaging dataResectionTumor recurrenceRadiation therapy03 medical and health sciences0302 clinical medicinePositron emission tomography030220 oncology & carcinogenesisMedicineSurgeryNeurology (clinical)Radiologybusiness030217 neurology & neurosurgeryGlioblastomaWorld Neurosurgery
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