0000000000896737

AUTHOR

Nicola Toschi

showing 2 related works from this author

Physics, Techniques and Review of Neuroradiological Applications of Diffusion Kurtosis Imaging (DKI)

2016

In recent years many papers about diagnostic applications of diffusion tensor imaging (DTI) have been published. This is because DTI allows to evaluate in vivo and in a non-invasive way the process of diffusion of water molecules in biological tissues. However, the simplified description of the diffusion process assumed in DTI does not permit to completely map the complex underlying cellular components and structures, which hinder and restrict the diffusion of water molecules. These limitations can be partially overcome by means of diffusion kurtosis imaging (DKI). The aim of this paper is the description of the theory of DKI, a new topic of growing interest in radiology. DKI is a higher or…

Diffusion tensor imaging (DTI)computer.software_genreSensitivity and Specificity030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineSettore MED/36 - Diagnostica per Immagini e RadioterapiaImage Interpretation Computer-AssistedHumansPreprocessorRadiology Nuclear Medicine and imagingMagnetic resonance imaging (MRI)Diffusion (business)DKIDiffusion Kurtosis ImagingParametric statisticsPhysicsBrain DiseasesDiffusion weighted imaging (DWI)Reproducibility of ResultsBrainSettore MED/37 - NeuroradiologiaImage EnhancementWhite MatterSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Acquisition ProtocolDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingNeuroradiologyDiffusion processDTIDWI NeuroradiologyDiffusional kurtosis imaging (DKI)Settore MED/26 - NeurologiaNeurology (clinical)Data miningBrain; Diffusion tensor imaging (DTI); Diffusion weighted imaging (DWI); Diffusional kurtosis imaging (DKI); Magnetic resonance imaging (MRI); NeuroradiologycomputerAlgorithms030217 neurology & neurosurgeryMRIDiffusion MRIClinical Neuroradiology
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Advanced computation in cardiovascular physiology: New challenges and opportunities

2021

Recent developments in computational physiology have successfully exploited advanced signal processing and artificial intelligence tools for predicting or uncovering characteristic features of physiological and pathological states in humans. While these advanced tools have demonstrated excellent diagnostic capabilities, the high complexity of these computational 'black boxes’ may severely limit scientific inference, especially in terms of biological insight about both physiology and pathological aberrations. This theme issue highlights current challenges and opportunities of advanced computational tools for processing dynamical data reflecting autonomic nervous system dynamics, with a speci…

Computer scienceGeneral MathematicsComputationGeneral Physics and AstronomyelectrocardiogramMachine learningcomputer.software_genreComputer-AssistedHeart RateArtificial IntelligenceHumansInterpretabilitySignal processingbusiness.industryDeep learningGeneral Engineeringheart rate variabilitydeep learningSignal Processing Computer-Assistedcardiology; deep learning; electrocardiogram; heart rate variability; interpretability; respiration; Heart Rate; Humans; Nonlinear Dynamics; Signal Processing Computer-Assisted; Algorithms; Artificial IntelligenceCardiovascular physiologyComputational physiologyNonlinear DynamicscardiologySignal ProcessingArtificial intelligencebusinessinterpretabilitycomputerrespirationAlgorithms
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