Search results for "automate"

showing 10 items of 245 documents

A smart and operator independent system to delineate tumours in Positron Emission Tomography scans

2018

Abstract Positron Emission Tomography (PET) imaging has an enormous potential to improve radiation therapy treatment planning offering complementary functional information with respect to other anatomical imaging approaches. The aim of this study is to develop an operator independent, reliable, and clinically feasible system for biological tumour volume delineation from PET images. Under this design hypothesis, we combine several known approaches in an original way to deploy a system with a high level of automation. The proposed system automatically identifies the optimal region of interest around the tumour and performs a slice-by-slice marching local active contour segmentation. It automa…

Lung NeoplasmsComputer sciencemedicine.medical_treatmentPET imagingPattern Recognition Automated030218 nuclear medicine & medical imaging0302 clinical medicineNeoplasmsImage Processing Computer-AssistedSegmentationDiagnosis Computer-AssistedNeoplasm MetastasisRadiation treatment planningSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniObserver VariationActive contour modelmedicine.diagnostic_testBrain NeoplasmsPhantoms ImagingComputer Science ApplicationsHead and Neck NeoplasmsPositron emission tomography030220 oncology & carcinogenesis18F-fluoro-2-deoxy-d-glucoseAlgorithms18F-fluoro-2-deoxy-d-glucose and 11C-labeled methionine PET imagingSimilarity (geometry)Health InformaticsSensitivity and SpecificityNOActive contour algorithm03 medical and health sciencesFluorodeoxyglucose F18Predictive Value of TestsRegion of interestmedicineHumansFalse Positive ReactionsRetrospective Studies18F-fluoro-2-deoxy-d-glucose 11C-labeled methionine PET imaging Active contour algorithm Biological target volume Cancer segmentationbusiness.industryRadiotherapy Planning Computer-Assisted11C-labeled methionineReproducibility of ResultsPattern recognitionGold standard (test)Cancer segmentationRadiation therapyBiological target volumePositron-Emission TomographyArtificial intelligenceTomography X-Ray ComputedbusinessSoftwareComputers in Biology and Medicine
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Fuzzy motion control strategy for cooperation of multiple automated vehicles with passengers comfort

2008

This paper considers motion control for a cooperative system of automated passenger vehicles. It develops a cooperative scheme based on a decentralized planning algorithm which considers the vehicles in an initial open chain configuration. In this scheme the trajectories are intersections-free, and each trajectory is planned independently of the others. To ensure the stabilization of each vehicle in the planned trajectory, a fuzzy closed loop motion control is presented, where, based on the properties of the Fuzzy maps, the Lyapunov’s stability of the motion errors is demonstrated for all the vehicles. Based on the ISO 2631-1 standard, the saturation property of the Fuzzy maps guarantees lo…

Lyapunov functionEngineeringAdaptive controlbusiness.industryControl engineeringBody movementFuzzy control systemMotion controlAutomated Vehicles Cooperation Fuzzy Control Lyapunov's stability Motion control passengers comfortFuzzy logicComputer Science::Roboticssymbols.namesakeSettore ING-INF/04 - AutomaticaFuzzy Control motion control ground vehicles passenger comfortControl and Systems EngineeringControl theoryTrajectorysymbolsElectrical and Electronic EngineeringDecentralized planningbusinessAutomatica
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A Multicentre Pilot Study of a Two-Tier Newborn Sickle Cell Disease Screening Procedure with a First Tier Based on a Fully Automated MALDI-TOF MS Pla…

2019

The reference methods used for sickle cell disease (SCD) screening usually include two analytical steps: a first tier for differentiating haemoglobin S (HbS) heterozygotes, HbS homozygotes and β-thalassemia from other samples, and a confirmatory second tier. Here, we evaluated a first-tier approach based on a fully automated matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) platform with automated sample processing, a laboratory information management system and NeoSickle® software for automatic data interpretation. A total of 6701 samples (with high proportions of phenotypes homozygous (FS) or heterozygous (FAS) for the inherited genes for sickle h…

MALDI-TOFPediatricsmedicine.medical_specialtythalassemia[SDV]Life Sciences [q-bio]Sample (statistics)01 natural sciencesArticle03 medical and health sciencesImmunology and Microbiology (miscellaneous)preventionmedicineDisease Screening Procedure030304 developmental biologymass spectrometry0303 health sciencesNewborn screeningbusiness.industryMALDI-TOF; sickle cell disease; newborn screening; mass spectrometry; thalassemia; preventionnewborn screening010401 analytical chemistrylcsh:RJ1-570Obstetrics and GynecologyData interpretationlcsh:Pediatrics0104 chemical sciencesMatrix-assisted laser desorption/ionizationFully automatedSickle haemoglobinPediatrics Perinatology and Child Healthsickle cell diseaseSample collectionbusinessInternational Journal of Neonatal Screening
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Smart River : Towards Efficient Cooperative Autonomous Inland Navigation

2022

In recent years, inland waterway transport has witnessed increasing attention from France and many European countries. However, this mode of transport lacks flexibility, has an aging infrastructure, and the current ships are not adapted to an increase in transport capacity ensuring the safety of vessels and goods as well as reliable and constant delivery times. Therefore, inland transport must go through an organizational and technical renovation specific to its particular environment in order to hope to compete with land transport.In this thesis, we propose developing a smart river ecosystem that focuses on three principal axes: (i) automatic inland infrastructure, (ii) autonomous inland s…

Machine Learning[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]ConnectivityConnectivitéSystèmes de transport intelligents coopératifsInternet des bateauxInternet of ShipsEcluses automatiséesCooperative Intelligent Transportation SystemsAutonomous ShipsAutomated locksBateaux AutonomesApprentissage machine
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Reference standard space hippocampus labels according to the European Alzheimer's Disease Consortium–Alzheimer's Disease Neuroimaging Initiative harm…

2017

Abstract Introduction A harmonized protocol (HarP) for manual hippocampal segmentation on magnetic resonance imaging (MRI) has recently been developed by an international European Alzheimer's Disease Consortium–Alzheimer's Disease Neuroimaging Initiative project. We aimed at providing consensual certified HarP hippocampal labels in Montreal Neurological Institute (MNI) standard space to serve as reference in automated image analyses. Methods Manual HarP tracings on the high-resolution MNI152 standard space template of four expert certified HarP tracers were combined to obtain consensual bilateral hippocampus labels. Utility and validity of these reference labels is demonstrated in a simple …

Magnetic Resonance Imaging/methods/standardsMaleJaccard indexEpidemiologyComputer sciencemethods [Pattern Recognition Automated]Image ProcessingAutomated/methods/standardsHippocampusPattern Recognition Automatedddc:616.89methods [Magnetic Resonance Imaging]0302 clinical medicinemethods [Image Processing Computer-Assisted]Image Processing Computer-AssistedComputer-Assisted/methods/standardsHARPdiagnostic imaging [Hippocampus]Health Policy05 social sciencesOrgan SizeReference StandardsMagnetic Resonance ImagingHippocampal segmentationstandards [Image Processing Computer-Assisted]Psychiatry and Mental healthNeuroimaging/methods/standardsFemalemethods [Neuroimaging]Hippocampus/diagnostic imagingAlzheimer's Disease Neuroimaging InitiativeAlzheimer Disease/diagnostic imagingNeuroimagingPattern Recognition050105 experimental psychology03 medical and health sciencesCellular and Molecular NeuroscienceDevelopmental NeuroscienceNeuroimagingAlzheimer DiseaseHumans0501 psychology and cognitive sciencesddc:610Reference standardsAgedProtocol (science)standards [Magnetic Resonance Imaging]business.industryPattern recognitionGold standard (test)Neurology (clinical)Artificial intelligenceGeriatrics and Gerontologybusinessdiagnostic imaging [Alzheimer Disease]standards [Pattern Recognition Automated]Neurosciencestandards [Neuroimaging]030217 neurology & neurosurgeryAlzheimer's & Dementia
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Non-negative blind source separation techniques for tumor tissue typing using HR-MAS signals.

2010

Given High Resolution Magic Angle Spinning (HR-MAS) signals from several glioblastoma tumor subjects, the goal is to differentiate between tumor tissue types by separating the different sources that contribute to the profile of each spectrum. Blind source separation techniques are applied for obtaining characteristic profiles for necrosis, high cellular tumor and border tumor tissue, and providing the contribution (abundance) of each tumor tissue to the profile of the spectra. The problem is formulated as a non-negative source separation problem. We illustrate the effectiveness of the proposed methods and we analyze to which extent the dimension of the input space could influence the perfor…

Magnetic Resonance SpectroscopyComputer scienceFeature extractionBlind signal separationSensitivity and SpecificitySpectral linePattern Recognition AutomatedNuclear magnetic resonanceDimension (vector space)medicineSource separationMagic angle spinningBiomarkers TumorHumansTypingDiagnosis Computer-Assistedmedicine.diagnostic_testArtificial neural networkbusiness.industryBrain NeoplasmsReproducibility of ResultsMagnetic resonance imagingPattern recognitionmedicine.diseaseTumor tissueArtificial intelligencebusinessGlioblastomaAlgorithmsGlioblastoma
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Ranking Series of Cancer-Related Gene Expression Data by Means of the Superposing Significant Interaction Rules Method

2020

The Superposing Significant Interaction Rules (SSIR) method is a combinatorial procedure that deals with symbolic descriptors of samples. It is able to rank the series of samples when those items are classified into two classes. The method selects preferential descriptors and, with them, generates rules that make up the rank by means of a simple voting procedure. Here, two application examples are provided. In both cases, binary or multilevel strings encoding gene expressions are considered as descriptors. It is shown how the SSIR procedure is useful for ranking the series of patient transcription data to diagnose two types of cancer (leukemia and prostate cancer) obtaining Area Under Recei…

Male0301 basic medicineKey genesComputer sciencelcsh:QR1-502Binary numberBiochemistrylcsh:MicrobiologyArticlePattern Recognition AutomatedStructure-Activity Relationship03 medical and health sciencesBig data0302 clinical medicinerankingData MiningHumanscancergene expressionsRelated geneCàncerMolecular BiologyOligonucleotide Array Sequence AnalysisCancerPròstata -- CàncerLeukemiaReceiver operating characteristicbusiness.industryGene Expression ProfilingleukemiaProstatic NeoplasmsLeucèmiaDades massivesPattern recognitionprostate cancerExpressió gènicaSSIR method030104 developmental biologyROC Curvemultilevel fingerprintsExpression dataData Interpretation Statistical030220 oncology & carcinogenesisProstate -- CancerArtificial intelligenceGene expressionbusinessAlgorithms
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Workflow-centred open-source fully automated lung volumetry in chest CT

2019

Aim To develop a robust open-source method for fully automated extraction of total lung capacity (TLC) from computed tomography (CT) images and to demonstrate its integration into the clinical workflow. Materials and methods Using only open-source software, an algorithm was developed based on a region-growing method that does not require manual interaction. Lung volumes calculated from reconstructions with different kernels (TLCCT) were assessed. To validate the algorithm calculations, the results were correlated to TLC measured by pulmonary function testing (TLCPFT) in a subgroup of patients for which this information was available within 3 days of the CT examination. Results A total of 28…

MaleChest ct030218 nuclear medicine & medical imagingPulmonary function testing03 medical and health sciencesImaging Three-Dimensional0302 clinical medicineHumansMedicineRadiology Nuclear Medicine and imagingSegmentationLung volumesRetrospective Studiesbusiness.industryGeneral MedicineMiddle Agedrespiratory systemRespiratory Function Testsrespiratory tract diseasesWorkflowOpen sourceFully automated030220 oncology & carcinogenesisLung volumetryRadiographic Image Interpretation Computer-AssistedFemaleRadiography ThoracicLung Volume MeasurementsTomography X-Ray ComputedNuclear medicinebusinessAlgorithmsSoftwareClinical Radiology
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A supervised learning framework of statistical shape and probability priors for automatic prostate segmentation in ultrasound images

2013

Prostate segmentation aids in prostate volume estimation, multi-modal image registration, and to create patient specific anatomical models for surgical planning and image guided biopsies. However, manual segmentation is time consuming and suffers from inter-and intra-observer variabilities. Low contrast images of trans rectal ultrasound and presence of imaging artifacts like speckle, micro-calcifications, and shadow regions hinder computer aided automatic or semi-automatic prostate segmentation. In this paper, we propose a prostate segmentation approach based on building multiple mean parametric models derived from principal component analysis of shape and posterior probabilities in a multi…

MaleComputer sciencePosterior probabilityScale-space segmentationImage registrationHealth InformaticsSensitivity and SpecificityPattern Recognition AutomatedArtificial IntelligenceImage Interpretation Computer-AssistedHumansRadiology Nuclear Medicine and imagingComputer visionSegmentationUltrasonographyRadiological and Ultrasound TechnologySegmentation-based object categorizationbusiness.industryProstateProstatic NeoplasmsReproducibility of ResultsPattern recognitionImage segmentationImage EnhancementComputer Graphics and Computer-Aided DesignSpectral clusteringActive appearance modelData Interpretation StatisticalComputer Vision and Pattern RecognitionArtificial intelligencebusinessAlgorithmsMedical Image Analysis
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Training labels for hippocampal segmentation based on the EADC-ADNI harmonized hippocampal protocol

2015

Abstract Background The European Alzheimer's Disease Consortium and Alzheimer's Disease Neuroimaging Initiative (ADNI) Harmonized Protocol (HarP) is a Delphi definition of manual hippocampal segmentation from magnetic resonance imaging (MRI) that can be used as the standard of truth to train new tracers, and to validate automated segmentation algorithms. Training requires large and representative data sets of segmented hippocampi. This work aims to produce a set of HarP labels for the proper training and certification of tracers and algorithms. Methods Sixty-eight 1.5 T and 67 3 T volumetric structural ADNI scans from different subjects, balanced by age, medial temporal atrophy, and scanner…

MaleEpidemiologyIntraclass correlationpathology [Cognitive Dysfunction]methods [Pattern Recognition Automated]Hippocampal formationHippocampusFunctional LateralityPattern Recognition Automatedpathology [Alzheimer Disease]ddc:616.89methods [Magnetic Resonance Imaging]methods [Image Processing Computer-Assisted]Image Processing Computer-AssistedSegmentationHARPAged 80 and overmedicine.diagnostic_testHealth PolicyOrgan SizeMiddle AgedMagnetic Resonance Imaginginstrumentation [Magnetic Resonance Imaging]Temporal LobePsychiatry and Mental healthFemalePsychologymethods [Neuroimaging]Algorithmsmethods [Imaging Three-Dimensional]anatomy & histology [Hippocampus]educationNeuroimagingTemporal lobeCellular and Molecular NeuroscienceImaging Three-DimensionalDevelopmental NeuroscienceNeuroimagingAlzheimer DiseasemedicineHumansCognitive Dysfunctionddc:610AgedProtocol (science)business.industryReproducibility of ResultsMagnetic resonance imagingpathology [Temporal Lobe]pathology [Hippocampus]Neurology (clinical)Geriatrics and GerontologyAtrophyNuclear medicinebusinessNeuroscience
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