Search results for "texture analysi"

showing 10 items of 28 documents

Effects of Interobserver Variability on 2D and 3D CT- and MRI-Based Texture Feature Reproducibility of Cartilaginous Bone Tumors

2021

AbstractThis study aims to investigate the influence of interobserver manual segmentation variability on the reproducibility of 2D and 3D unenhanced computed tomography (CT)- and magnetic resonance imaging (MRI)-based texture analysis. Thirty patients with cartilaginous bone tumors (10 enchondromas, 10 atypical cartilaginous tumors, 10 chondrosarcomas) were retrospectively included. Three radiologists independently performed manual contour-focused segmentation on unenhanced CT and T1-weighted and T2-weighted MRI by drawing both a 2D region of interest (ROI) on the slice showing the largest tumor area and a 3D ROI including the whole tumor volume. Additionally, a marginal erosion was applied…

Artificial intelligenceFuture studiesIntraclass correlationChondrosarcomaBone NeoplasmsArticleRegion of interestNeoplasmsArtificial intelligence Chondroma Chondrosarcoma Neoplasms Radiomics Texture analysisHumansMedicineRadiology Nuclear Medicine and imagingSegmentationTexture featureRetrospective StudiesObserver VariationReproducibilityRadiomicsRadiological and Ultrasound Technologymedicine.diagnostic_testbusiness.industryReproducibility of ResultsMagnetic resonance imagingmedicine.diseaseMagnetic Resonance ImagingComputer Science ApplicationsTexture analysisFeature (computer vision)ChondrosarcomaTomography X-Ray ComputedbusinessNuclear medicineChondromaChondromaJournal of Digital Imaging
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A Predictive System to Classify Preoperative Grading of Rectal Cancer Using Radiomics Features

2022

Although preoperative biopsy of rectal cancer (RC) is an essential step for confirmation of diagnosis, it currently fails to provide prognostic information to the clinician beyond a rough estimation of tumour grade. In this study we used a risk classification to stratified patient in low-risk and high-risk patients in relation to the disease free survival and the overall survival using histopathological post-operative features. The purpose of this study was to evaluate if low-risk and high-risk RC can be distinguished using a CT-based radiomics model. We retrospectively reviewed the preoperative abdominal contrast-enhanced CT of 40 patients with RC. CT portal-venous phase was used for manua…

Computed tomography Radiomics Rectal cancer Texture analysis
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Complex networks : application for texture characterization and classification

2008

This article describes a new method and approch of texture characterization. Using complex network representation of an image, classical and derived (hierarchical) measurements, we presente how to have good performance in texture classification. Image is represented by a complex networks : one pixel as a node. Node degree and clustering coefficient, using with traditionnal and extended hierarchical measurements, are used to characterize ”organisation” of textures.

Computer engineering. Computer hardwareTexture compressionComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONComplex networksImage processingTexture (geology)TK7885-7895Image textureImage processingAnàlisi de texturaProcesamiento de imágenestexture analysisClustering coefficientAnálisis de texturaRedes complejasPixelbusiness.industryNode (networking)Pattern recognitionProcessament d'imatgescomplex networksQA75.5-76.95Xarxes complexesComplex networkTexture analysisElectronic computers. Computer scienceComputer Science::Computer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareELCVIA: electronic letters on computer vision and image analysis
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Breast dynamic contrast-enhanced-magnetic resonance imaging and radiomics: State of art

2020

Breast cancer represents the most common malignancy in women, being one of the most frequent cause of cancer-related mortality. Ultrasound, mammography, and magnetic resonance imaging (MRI) play a pivotal role in the diagnosis of breast lesions, with different levels of accuracy. Particularly, dynamic contrast-enhanced MRI has shown high diagnostic value in detecting multifocal, multicentric, or contralateral breast cancers. Radiomics is emerging as a promising tool for quantitative tumor evaluation, allowing the extraction of additional quantitative data from radiological imaging acquired with different modalities. Radiomics analysis may provide novel information through the quantification…

Dynamic contrastNuclear magnetic resonancemedicine.diagnostic_testRadiomicsbusiness.industrymedicineState of artMagnetic resonance imagingRadiomics Texture analysis Magnetic resonance imaging Dynamic contrast-enhanced-magnetic resonance imaging Breast CancerGeneral MedicinebusinessSettore MED/36 - Diagnostica Per Immagini E Radioterapia
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Radiomics Analyses of Schwannomas in the Head and Neck: A Preliminary Analysis

2022

The purpose of this preliminary study was to evaluate the differences in Magnetic Resonance Imaging (MRI)-based radiomics analysis between cerebellopontine angle neurinomas and schwannomas originating from other locations in the neck spaces. Twenty-six patients with available MRI exams and head and neck schwannomas were included. Lesions were manually segmented on the precontrast and postcontrast T1 sequences. The radiomics features were extracted by using PyRadiomics software, and a total of 120 radiomics features were obtained from each segmented tumor volume. An operator-independent hybrid descriptive‐inferential method was adopted for the selection and reduction of the features, while d…

Head and neck cancer Magnetic resonance imaging Radiomics Texture analysis
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Etude et modélisation du comportement des gouttelettes de produits phytosanitaires sur les feuilles de vignes par imagerie ultra-rapide et analyse de…

2013

In the domain of vineyard precision spraying research, one of the most importantobjectives is to minimize the volume of phytosanitary products ejected bya sprayer in order to be more environmentally respectful with more effectivevine leaf treatments. Unfortunaltely, even if lot of works have been carriedout at a parcel scale, mainly on losses caused by drift, less works have beencarried out at the leaf scale in order to understand which parameters influencethe spray quality. Since few years, recent improvements in image processing,sensitivity of imaging systems and cost reduction have increased the interestof high-speed imaging techniques. Analyzing the behavior of droplets afterimpact with…

High-speed imaging[SPI.OTHER]Engineering Sciences [physics]/Other[SDV.SA]Life Sciences [q-bio]/Agricultural sciences[SDV.SA] Life Sciences [q-bio]/Agricultural sciences[ SPI.OTHER ] Engineering Sciences [physics]/Other[SPI.OTHER] Engineering Sciences [physics]/OtherTrackingImagerie rapideAnalyse de texturesTexture analysisPulvérisationSprayingSuivi d’objets[ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences
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Development of an ultrasound-based muscle texture analysis as a potential imaging biomarker for frailty phenotype

2018

Las herramientas habituales para evaluar la fragilidad muestran, entre otras características, una baja sensibilidad y un bajo valor predictivo positivo. Es por eso que, en este estudio prospectivo-retrospectivo, nos preguntamos si es posible identificar y desarrollar biomarcadores cuantitativos a partir de imágenes de ultrasonido muscular, para la identificación de sujetos con riesgo de fragilidad. Para ello utlilizamos el análisis de textura de ecointensidad con ayuda del aprendizaje automático (machine learning, en inglés) como enfoque experimental para responder a esta pregunta. El proyecto se desarrolló en consulta externa, donde se realizó la ecografía muscular. Al final de la adquisic…

Machine LearningFrailtyUltrasoundDiagnóstico por imagenTexture AnalysisUltrasonidosInteligencia ArtificialEnvejecimiento de la poblaciónBiomarkers
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Differentiation between acute and chronic myocardial infarction by means of texture analysis of late gadolinium enhancement and cine cardiac magnetic…

2017

[EN] The purpose of this study was to differentiate acute from chronic myocardial infarction using machine learning techniques and texture features extracted from cardiac magnetic resonance imaging (MRI). The study group comprised 22 cases with acute myocardial infarction (AMI) and 22 cases with chronic myocardial infarction (CMI). Cine and late gadolinium enhancement (LGE) MRI were analyzed independently to differentiate AMI from CMI. A total of 279 texture features were extracted from predefined regions of interest (ROIs): the infarcted area on LGE MRI, and the entire myocardium on cine MRI. Classification performance was evaluated by a nested cross-validation approach combining a feature…

Malemedicine.medical_specialtySupport Vector MachineMyocardial InfarctionContrast MediaMagnetic Resonance Imaging CineInfarctionGadolinium030204 cardiovascular system & hematologySensitivity and Specificity030218 nuclear medicine & medical imagingDiagnosis DifferentialTECNOLOGIA ELECTRONICA03 medical and health sciences0302 clinical medicinePolynomial kernelCardiac magnetic resonance imagingmedicineHumansLate gadolinium enhancementRadiology Nuclear Medicine and imagingMyocardial infarctioncardiovascular diseasesCardiac MRIChronic myocardial infarctionReceiver operating characteristicmedicine.diagnostic_testbusiness.industryMyocardiumReproducibility of ResultsGeneral MedicineMiddle Agedmedicine.diseaseSupport vector machineClassification Myocardial infarctionROC CurveTexture analysisArea Under CurveAcute DiseaseChronic Diseasecardiovascular systemFemaleRadiologyNuclear medicinebusinessAlgorithmsMagnetic Resonance Angiography
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Everything matters: Molar microwear texture in goats (Capra aegagrus hircus) fed diets of different abrasiveness

2020

There is an ongoing discourse about whether or not external abrasives influence the microscopic wear in herbivore teeth, including a statement that “dust does not matter”. We submitted the maxillary and mandibular second molar of 28 goats (Capra aegagrus hircus) to dental microwear texture analysis (DMTA). The study animals were divided into four groups, which received diets of increasing phytolith-based abrasiveness (L: lucerne based pellets, very low phytolith abrasion diet, acting as control; G: grass-based pellets, medium abrasive phytolith diet; GR: grass and rice husk pellets, high abrasion phytolith diet), or a diet with added external abrasives (GRS: the GR diet with add…

Molar010506 paleontology10253 Department of Small AnimalsEvolutionPhytolith1904 Earth-Surface ProcessesGrazerGrit010502 geochemistry & geophysicsOceanography01 natural sciencesMesowearMesowearAnimal scienceBehavior and SystematicsGrazing1910 Oceanographymedia_common.cataloged_instanceEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesEarth-Surface Processesmedia_common2. Zero hungerEnamel paintbiology630 AgricultureEcologyPalaeontologyTooth wearPaleontologyEarthbiology.organism_classification1911 Paleontology1105 Ecology Evolution Behavior and SystematicsTexture analysisConnochaetes taurinusSurface ProcessesTooth wearPhytolithvisual_artvisual_art.visual_art_medium570 Life sciences; biologyGeologyGiraffa camelopardalis
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Automatic recognition of tree species from 3D point clouds of forest plots

2014

The objective of the thesis is the automatic recognition of tree species from Terrestrial LiDAR data. This information is essential for forest inventory. As an answer, we propose different recognition methods based on the 3D geometric texture of the bark.These methods use the following processing steps: a preprocessing step, a segmentation step, a feature extraction step and a final classification step. They are based on the 3D data or on depth images built from 3D point clouds of tree trunks using a reference surface.We have investigated and tested several segmentation approaches on depth images representing the geometric texture of the bark. These approaches have the disadvantages of over…

Reconnaissance de formes 3DInventaire forestierAnalyse de texture 3DTree species recognitionIdentification des espèces d’arbres3D geometric texture analysisForest inventory3D pattern recognition[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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