Search results for "Image Enhancement"

showing 10 items of 215 documents

Power estimation for non-standardized multisite studies

2016

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this…

Computer scienceCognitive Neurosciencecomputer.software_genreSensitivity and Specificity050105 experimental psychologyImaging phantomArticleSet (abstract data type)03 medical and health sciences0302 clinical medicineDistortionImage Interpretation Computer-AssistedCalibrationmedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumans0501 psychology and cognitive sciencesSegmentationComputer Simulation10. No inequalityScalingModels Statisticalmedicine.diagnostic_test05 social sciencesContrast (statistics)BrainReproducibility of ResultsMagnetic resonance imagingEquipment DesignScale factorImage EnhancementMagnetic Resonance ImagingUnited StatesEquipment Failure AnalysisEuropeNeurologyOrdinary least squaresData miningFunction and Dysfunction of the Nervous SystemArtifactscomputer030217 neurology & neurosurgeryAlgorithms
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Automatic skull stripping in MRI based on morphological filters and fuzzy c-means segmentation

2012

In this paper a new automatic skull stripping method for T1-weighted MR image of human brain is presented. Skull stripping is a process that allows to separate the brain from the rest of tissues. The proposed method is based on a 2D brain extraction making use of fuzzy c-means segmentation and morphological operators applied on transversal slices. The approach is extended to the 3D case, taking into account the result obtained from the preceding slice to solve the organ splitting problem. The proposed approach is compared with BET (Brain Extraction Tool) implemented in MRIcro software.

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSensitivity and SpecificityFuzzy logicPattern Recognition AutomatedFuzzy LogicImage Interpretation Computer-AssistedmedicineHumansSegmentationComputer visionSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionimedicine.diagnostic_testSkull Stripping Fuzzy C-means Morphological Filters.business.industrySkullProcess (computing)BrainReproducibility of ResultsMagnetic resonance imagingImage segmentationImage EnhancementMagnetic Resonance ImagingSubtraction TechniquePattern recognition (psychology)Skull strippingArtificial intelligenceMr imagesbusinessAlgorithms2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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Bias artifact suppression on MR volumes.

2007

RF-Inhomogeneity correction is a relevant research topic in the field of Magnetic Resonance Imaging (MRI). A volume corrupted by this artifact exhibits nonuni- form illumination both inside a single slice and between adjacent ones. In this work a bias correction technique is presented, which suppresses this artifact on MR vol- umes scanned from different body parts without any a-priori hypothesis on the artifact model. Theoretical foundations of the method are reported together with experimental results and a comparison is presented with both the 2D version of the algorithm and other techniques that are widely used in MRI literature.

Computer scienceHealth InformaticsSensitivity and SpecificityImaging Three-DimensionalBiasImage Interpretation Computer-AssistedmedicineComputer visionRF-Inhomogeneity Bias Artifact Illumination correction MR Image Homomorphic filterSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniArtifact (error)medicine.diagnostic_testbusiness.industryReproducibility of ResultsMagnetic resonance imagingImage EnhancementMagnetic Resonance ImagingComputer Science ApplicationsArtifact suppressionArtificial intelligenceMr imagesbusinessArtifactsSoftwareAlgorithmsVolume (compression)Computer methods and programs in biomedicine
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Divisive normalization image quality metric revisited.

2010

Structural similarity metrics and information-theory-based metrics have been proposed as completely different alternatives to the traditional metrics based on error visibility and human vision models. Three basic criticisms were raised against the traditional error visibility approach: (1) it is based on near-threshold performance, (2) its geometric meaning may be limited, and (3) stationary pooling strategies may not be statistically justified. These criticisms and the good performance of structural and information-theory-based metrics have popularized the idea of their superiority over the error visibility approach. In this work we experimentally or analytically show that the above critic…

Computer sciencebusiness.industryImage qualityMachine visionPoolingNormalization (image processing)Wavelet transformImage processingImage enhancementMachine learningcomputer.software_genreAtomic and Molecular Physics and OpticsImage contrastElectronic Optical and Magnetic MaterialsOpticsComputer Vision and Pattern RecognitionArtificial intelligencebusinesscomputerJournal of the Optical Society of America. A, Optics, image science, and vision
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Restoration and Enhancement of Historical Stereo Photos Through Optical Flow

2021

Restoration of digital visual media acquired from repositories of historical photographic and cinematographic material is of key importance for the preservation, study and transmission of the legacy of past cultures to the coming generations. In this paper, a fully automatic approach to the digital restoration of historical stereo photographs is proposed. The approach exploits the content redundancy in stereo pairs for detecting and fixing scratches, dust, dirt spots and many other defects in the original images, as well as improving contrast and illumination. This is done by estimating the optical flow between the images, and using it to register one view onto the other both geometrically …

Computer sciencemedia_common.quotation_subjectNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flow02 engineering and technologyConsistency (database systems)Image restoration0202 electrical engineering electronic engineering information engineeringRedundancy (engineering)Contrast (vision)Computer visionImage restorationmedia_commonSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabusiness.industryOptical flow021001 nanoscience & nanotechnologySensor fusionStereo matchingTransmission (telecommunications)Image denoisingImage enhancementGradient filtering020201 artificial intelligence & image processingArtificial intelligence0210 nano-technologybusiness
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Morse Description and Geometric Encoding of Digital Elevation Maps

2004

Two complementary geometric structures for the topographic representation of an image are developed in this work. The first one computes a description of the Morse-topological structure of the image, while the second one computes a simplified version of its drainage structure. The topographic significance of the Morse and drainage structures of digital elevation maps (DEMs) suggests that they can been used as the basis of an efficient encoding scheme. As an application, we combine this geometric representation with an interpolation algorithm and lossless data compression schemes to develop a compression scheme for DEMs. This algorithm achieves high compression while controlling the maximum …

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingData_CODINGANDINFORMATIONTHEORYSensitivity and SpecificityPattern Recognition AutomatedPhysics::GeophysicsImaging Three-DimensionalCompression (functional analysis)Image Interpretation Computer-AssistedComputer SimulationComputer visionMorse theoryMathematicsLossless compressionbusiness.industryReproducibility of ResultsNumerical Analysis Computer-AssistedSignal Processing Computer-AssistedData CompressionImage EnhancementTopographic mapComputer Graphics and Computer-Aided DesignArtificial intelligencebusinessAlgorithmAlgorithmsSoftwareData compressionImage compressionInterpolationIEEE Transactions on Image Processing
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Mammographic images segmentation based on chaotic map clustering algorithm

2013

Background: This work investigates the applicability of a novel clustering approach to the segmentation of mammographic digital images. The chaotic map clustering algorithm is used to group together similar subsets of image pixels resulting in a medically meaningful partition of the mammography. Methods: The image is divided into pixels subsets characterized by a set of conveniently chosen features and each of the corresponding points in the feature space is associated to a map. A mutual coupling strength between the maps depending on the associated distance between feature space points is subsequently introduced. On the system of maps, the simulated evolution through chaotic dynamics leads…

Cooperative behaviorClustering algorithmsComputer scienceFeature vectorCorrelation clusteringPhysics::Medical PhysicsMass lesionsMicrocalcificationsImage processingBreast NeoplasmsDigital imageSegmentationBreast cancerImage Processing Computer-AssistedCluster AnalysisHumansRadiology Nuclear Medicine and imagingSegmentationComputer visionCluster analysisFeaturesPixelChaotic maps Clustering algorithms Cooperative behavior Segmentation Mammography Features Mass lesions Microcalcifications Breast cancerbusiness.industrySegmentation-based object categorizationCalcinosisSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Radiographic Image EnhancementChaotic mapsRadiology Nuclear Medicine and imagingComputer Science::Computer Vision and Pattern RecognitionFemaleArtificial intelligencebusinessAlgorithmsMammographyResearch Article
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Anatomical variants and anomalies of the coronary tree studied with MDCT coronary angiography

2010

Le anomalie delle arterie coronariche sono presenti alla nascita nella maggior parte dei casi asintomatiche ma possono manifestarsi con sintomatologia severa quale angina pectoris o addirittura l’arresto cardiaco. L’angiografia coronarica mediante tomografia computerizzata multistrato (TCMS) permette, tramite ricostruzioni multiplanari secondo piani curvilinei e riformattazioni 3D, la visualizzazione dell’albero coronarico e delle sue varianti ed anomalie in maniera non invasiva, fornendo migliore e più accurata alternativa alla angiografia coronarica (AC). Lo scopo di questo pictorial consiste nella descrizione mediante immagini TCMS con ricostruzioni multiplanari e 3D delle principali var…

Coronary angiographymedicine.medical_specialtyFistulaCoronary anomaliesCoronary Vessel AnomaliesFistulaAsymptomaticAnginaImaging Three-DimensionalHumansMedicineRadiology Nuclear Medicine and imagingcardiovascular diseasesNeuroradiologyCoronary variantsmedicine.diagnostic_testbusiness.industryMDCTInterventional radiologyGeneral Medicinemedicine.diseaseMiocardial bridgingRadiographic Image EnhancementCoronary arteriesmedicine.anatomical_structurecardiovascular systemTomographyRadiologymedicine.symptomcoronary angiographyTomography X-Ray ComputedbusinessSettore MED/36 - Diagnostica Per Immagini E RadioterapiaMDCT; coronary angiography; Coronary anomalies; Coronary variants; Miocardial bridging; FistulaMDCT coronary angiography Coronary anomalies Coronary variants Miocardial bridging Fistula
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Measuring Spatiotemporal Dependencies in Bivariate Temporal Random Sets with Applications to Cell Biology

2008

Analyzing spatiotemporal dependencies between different types of events is highly relevant to many biological phenomena (e.g., signaling and trafficking), especially as advances in probes and microscopy have facilitated the imaging of dynamic processes in living cells. For many types of events, the segmented areas can overlap spatially and temporally, forming random clumps. In this paper, we model the binary image sequences of two different event types as a realization of a bivariate temporal random set and propose a nonparametric approach to quantify spatial and spatiotemporal interrelations using the pair correlation, cross-covariance, and the Ripley K functions. Based on these summary st…

Covariance functionModels BiologicalSensitivity and SpecificityPattern Recognition Automated03 medical and health sciences0302 clinical medicineArtificial IntelligenceImage Interpretation Computer-AssistedCells CulturedIndependence (probability theory)030304 developmental biologyMathematics0303 health sciencesModels Statisticalbusiness.industryStochastic processApplied MathematicsNonparametric statisticsReproducibility of ResultsEstimatorImage EnhancementEndocytosisTemporal databaseMicroscopy FluorescenceComputational Theory and Mathematics[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]Computer Vision and Pattern RecognitionArtificial intelligenceCross-covariancebusinessAlgorithms030217 neurology & neurosurgerySoftwareRealization (probability)IEEE Transactions on Pattern Analysis and Machine Intelligence
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A completely automated CAD system for mass detection in a large mammographic database.

2006

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing secon…

Databases FactualInformation Storage and RetrievalReproducibility of ResultsBreast NeoplasmsSensitivity and SpecificityNeural networkPattern Recognition AutomatedRadiographic Image EnhancementBreast cancerTextural featuresRadiology Information SystemsImage processingComputer-aided detection (CAD)Artificial IntelligenceCluster AnalysisDatabase Management SystemsHumansRadiographic Image Interpretation Computer-AssistedFemaleBreast cancer; Computer-aided detection (CAD); Image processing; Mammographic mass detection; Neural network; Textural featuresMammographic mass detectionAlgorithmsMammographyMedical physics
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