Search results for "Texture analysis"

showing 10 items of 25 documents

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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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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Protocol for the Definition of a Multi-Spectral Sensor for Specific Foliar Disease Detection: Case of “Flavescence Dorée”

2018

Flavescence Doree (FD) is a contagious and incurable grapevine disease that can be perceived on leaves. In order to contain its spread, the regulations obligate winegrowers to control each plant and to remove the suspected ones. Nevertheless, this monitoring is performed during the harvest and mobilizes many people during a strategic period for viticulture. To solve this problem, we aim to develop a Multi-Spectral (MS) imaging device ensuring an automated grapevine disease detection solution. If embedded on a UAV, the tool can provide disease outbreaks locations in a geographical information system allowing localized and direct treatment of infected vines. The high-resolution MS camera aims…

0106 biological sciences[SDE] Environmental SciencesDisease detectionComputer science[SDV]Life Sciences [q-bio]Multispectral imageradiometric/geometric correctionsFeature selectionMulti spectral01 natural sciencesfeature selection[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biologytexture analysisProtocol (science)Artificial neural networkbusiness.industrymultispectral sensorOutbreakPattern recognition04 agricultural and veterinary sciencesFlavescence Dorée3. Good health[SDV] Life Sciences [q-bio]Identification (information)classification[SDE]Environmental Sciences040103 agronomy & agriculture0401 agriculture forestry and fisheriesFlavescence doréeArtificial intelligencebusiness010606 plant biology & botany
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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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Analyse spectrale et texturale de données à haute résolution pour la détection automatique des maladies de la vigne

2019

‘Flavescence dorée’ is a contagious and incurable disease present on the vine leaves. In order to contain the infection, the regulations require growers to control each of the vine rows and to remove the suspect vine plants. This monitoring is done on foot during the harvest and mobilizes many people during a strategic period for viticulture. In order to solve this problem, the DAMAV project (Automatic detection of Vine Diseases) aims to develop a solution for automated detection of vine diseases using a micro-drone. The goal is to offer a turnkey solution for wine growers. This tool will allow the search for potential foci, and then more generally any type of vine diseases detectable on th…

capteur multispectralmultispectral sensor[SDV]Life Sciences [q-bio]indices de végétationalgorithmes génétiquesgrapevine diseases detectiondétection des maladies de la vignegenetic algorithms[SDV] Life Sciences [q-bio]successive projections algorithmfeature selectionclassificationalgorithmes de projections successivesvegetation indicesanalyse de texturesélection de caractéristiquestexture analysis
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Leaf surface roughness characterization by image processing

2013

International audience

[SDV] Life Sciences [q-bio][SDE] Environmental Sciencesleaf roughnessprecision agriculturecharacterization of the leaf surface[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal BiologyComputingMilieux_MISCELLANEOUSaccurate sprayingtexture analysisspectral 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 predicts survival of patients with advanced non-small cell lung cancer undergoing PD-1 blockade using Nivolumab

2019

Immune checkpoint blockade is an emerging anticancer strategy, and Nivolumab is a human mAb to PD-1 that is used in the treatment of a number of different malignancies, including non-small cell lung cancer (NSCLC), kidney cancer, urothelial carcinoma and melanoma. Although the use of Nivolumab prolongs survival in a number of patients, this treatment is hampered by high cost. Therefore, the identification of predictive markers of response to treatment in patients is required. In this context, PD-1/PDL1 blockade antitumor effects occur through the reactivation of a pre-existing immune response, and the efficacy of these effects is strictly associated with the presence of necrosis, hypoxia an…

0301 basic medicineOncologyCancer Researchmedicine.medical_specialtySurvivalImmunology03 medical and health sciences0302 clinical medicineNon-small cell lung cancerInternal medicinemedicineProgression-free survivalLung cancerPathologicalProgrammed cell death protein 1business.industryMelanomaRetrospective cohort studyArticlesmedicine.diseaseBlockade030104 developmental biologyNivolumabOncologyTexture analysis030220 oncology & carcinogenesisNivolumabRadiomicbusinessKidney cancer
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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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