Search results for "SEGMENTATION"

showing 10 items of 674 documents

2016

AbstractMulticellular tumor spheroids (MCTSs) embedded in a matrix are re-emerging as a powerful alternative to monolayer-based cultures. The primary information gained from a three-dimensional model is the invasiveness of treatment-exposed MCTSs through the acquisition of light microscopy images. The amount and complexity of the acquired data and the bias arisen by their manual analysis are disadvantages calling for an automated, high-throughput analysis. We present a universal algorithm we developed with the scope of being robust enough to handle images of various qualities and various invasion profiles. The novelty and strength of our algorithm lie in: the introduction of a multi-step se…

0301 basic medicine03 medical and health sciencesMulticellular organism030104 developmental biologyMultidisciplinaryGentamicin protection assayTumor spheroidSegmentationBiologyBiological systemBioinformaticsScientific Reports
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Revealing community structures by ensemble clustering using group diffusion

2018

We propose an ensemble clustering approach using group diffusion to reveal community structures in data. We represent data points as a directed graph and assume each data point belong to single cluster membership instead of multiple memberships. The method is based on the concept of ensemble group diffusion with a parameter to represent diffusion depth in clustering. The ability to modulate the diffusion-depth parameter by varying it within a certain interval allows for more accurate construction of clusters. Depending on the value of the diffusion-depth parameter, the presented approach can determine very well both local clusters and global structure of data. At the same time, the ability …

0301 basic medicineComputer scienceProperty (programming)Markov chain02 engineering and technologyInterval (mathematics)03 medical and health sciencesdiffuusio (fysikaaliset ilmiöt)0202 electrical engineering electronic engineering information engineeringCluster (physics)SegmentationDiffusion (business)Cluster analysista113ta213diffusionDirected graph030104 developmental biologyData pointHardware and ArchitectureSignal Processingyhdyskuntarakenne020201 artificial intelligence & image processingsocial networkcommunity structureAlgorithmSoftwareInformation Systemsclustering
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Automatic detection of hemangiomas using unsupervised segmentation of regions of interest

2016

In this paper we compare the performances of three automatic methods of identifying hemangioma regions in images: 1) unsupervised segmentation using the Otsu method, 2) Fuzzy C-means clustering (FCM) and 3) an improved region growing algorithm based on FCM (RG-FCM). For each image, the starting point of the algorithms is a rectangular region of interest (ROI) containing the hemangioma. For computing the performances of each method, the ROIs had been manually labeled in 2 classes: pixels of hemangioma and pixels of non-hemangioma. The computed scores are given separately for each image, as well as global performances across all ROIs for both classes. The best classification of non-hemangioma…

0301 basic medicineComputer scienceScale-space segmentation02 engineering and technologyOtsu's methodHemangioma03 medical and health sciencessymbols.namesakeMinimum spanning tree-based segmentationRegion of interestHistogram0202 electrical engineering electronic engineering information engineeringmedicineComputer visionSegmentation-based object categorizationbusiness.industryPattern recognitionImage segmentationmedicine.diseaseStatistical classification030104 developmental biologyRegion growingsymbols020201 artificial intelligence & image processingArtificial intelligencebusiness2016 International Conference on Communications (COMM)
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Analysis of Microstructure of the Cardiac Conduction System Based on Three-Dimensional Confocal Microscopy

2016

The specialised conducting tissues present in the ventricles are responsible for the fast distribution of the electrical impulse from the atrio-ventricular node to regions in the subendocardial myocardium. Characterisation of anatomical features of the specialised conducting tissues in the ventricles is highly challenging, in particular its most distal section, which is connected to the working myocardium via Purkinje-myocardial junctions. The goal of this work is to characterise the architecture of the distal section of the Purkinje network by differentiating Purkinje cells from surrounding tissue, performing a segmentation of Purkinje fibres at cellular scale, and mathematically describin…

0301 basic medicineConfocal Microscopylcsh:Medicine030204 cardiovascular system & hematologylaw.inventionPurkinje Cells0302 clinical medicineAnimal CellslawMedicine and Health SciencesMyocyteSegmentationlcsh:ScienceMammalsMicroscopyMicroscopy ConfocalMultidisciplinaryLight MicroscopyHeartAnimal ModelsAnatomyVertebratesRabbitsCellular TypesAnatomyElectrical conduction system of the heartNetwork AnalysisResearch ArticleComputer and Information SciencesCell typeCardiac VentriclesHeart VentriclesMuscle TissueBiologyResearch and Analysis MethodsImaging data03 medical and health sciencesImaging Three-DimensionalModel OrganismsHeart Conduction SystemConfocal microscopyAnimalsComplex network analysisMuscle CellsMyocardiumlcsh:ROrganismsBiology and Life SciencesCell BiologyWheat germ agglutininBiological Tissue030104 developmental biologyAmniotesCardiovascular Anatomylcsh:QEndocardiumBiomedical engineeringPLOS ONE
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Brain-like large scale cognitive networks and dynamics

2018

A new approach to the study of the brain and its functions known as Human Connectomics has been recently established. Starting from magnetic resonance images (MRI) of brain scans, it is possible to identify the fibers that link brain areas and to build an adjacency matrix that connects these areas, thus creating the brain connectome. The topology of these networks provides a lot of information about the organizational structure of the brain (both structural and functional). Nevertheless this knowledge is rarely used to investigate the possible emerging brain dynamics linked to cognitive functions. In this work, we implement finite state models on neural networks to display the outcoming bra…

0301 basic medicineConnectomicsQuantitative Biology::Neurons and CognitionArtificial neural networkComputer sciencebusiness.industryGeneral Physics and AstronomyCognitionPattern recognitionCognitive network03 medical and health sciencesPhysics and Astronomy (all)030104 developmental biology0302 clinical medicineNeuroimagingConnectomeGeneral Materials ScienceSegmentationAdjacency matrixArtificial intelligenceMaterials Science (all)Physical and Theoretical Chemistrybusiness030217 neurology & neurosurgery
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Analysis of normal human retinal vascular network architecture using multifractal geometry

2017

AIM To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina. METHODS Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images, corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms, applying the standard box-counting method. Statistical analyse…

0301 basic medicineEarly detectionGeometryFundus (eye)03 medical and health scienceschemistry.chemical_compoundretinal vessel segmentationlcsh:OphthalmologyClinical ResearchMedicineSegmentationRetinal microvasculaturebusiness.industryRetinalMultifractal systemGeneralized dimensionsMultifractalRetinal vesselOphthalmology030104 developmental biologyMicrovascular NetworkRetinal image analysisStandard box-counting methodchemistryVascular networklcsh:RE1-994business
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PSPU-Net for Automatic Short Axis Cine MRI Segmentation of Left and Right Ventricles

2020

[EN] Characterization of the heart anatomy and function is mostly done with magnetic resonance image cine series. To achieve a correct characterization, the volume of the right and left ventricle need to be segmented, which is a timeconsuming task. We propose a new convolutional neural network architecture that combines U-net with PSP modules (PSPU-net) for the segmentation of left and right ventricle cavities and left ventricle myocardium in the diastolic frame of short-axis cine MRI images and compare its results against a classic 3D U-net architecture. We used a dataset containing 399 cases in total. The results showed higher quality results in both segmentation and final volume estimati…

0301 basic medicineLeft and rightComputer science030204 cardiovascular system & hematologyVolume estimationConvolutional neural networkU-netTECNOLOGIA ELECTRONICA03 medical and health sciencesSegmentation0302 clinical medicineVolume estimationmedicineSegmentationPSPmedicine.diagnostic_testbusiness.industryDeep learningMagnetic resonance imagingLeft ventricleCine mri030104 developmental biologymedicine.anatomical_structureVentricleRight ventricleNuclear medicinebusinessMRIVolume (compression)2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE)
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Study of Consumer Preferences in Regard to the Blonde Orange Cv. Washington Navel “Arancia Di Ribera PDO”

2016

Consumers’ attitude and preferences in regard to food ingre- dients, country of origin, social corporate responsibility toward the environment, and work conditions have changed over the last 10 years. Consumers are getting more educated and there- fore more sensitive around cultivation practices in agriculture and food processing, which increases concerns in regard to production practices in agriculture. Several studies have been conducted on consumers’ preferences about quality food, but not with regard to blonde oranges cv. Washington Navel culti- vated in southern Italy. This quality fruit is a niche product that achieved the Protected Designation of Origin (PDO) certifica- tion for high…

0301 basic medicineMarketing030109 nutrition & dieteticsbusiness.industryCertificationOrange (colour)PurchasingCountry of originCluster Analysis Consumer Preferences Preferences segmentation Purchase behaviour Quality fresh food03 medical and health sciencesGeographyAgricultureSettore AGR/01 - Economia Ed Estimo RuraleFood processingCorporate social responsibilityBusiness and International ManagementMarketingFood qualitybusinessFood Science
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Automatic monitoring system for the detection and evaluation of the evolution of hemangiomas

2016

In this paper we introduce an automatic monitoring system for the detection and the evaluation of the evolution of hemangiomas using a fuzzy logic system based on two parameters: area and redness. We have considered pairs of images (from two different moments in time) that show hemangiomas either evolving, stationary or regressing. The starting points of the algorithm are the rectangular regions of interest (ROI), manually selected for each of the two images, and automatically segmented using Fuzzy C-means. Using the area and the redness of the hemagiomas extracted with Fuzzy C-means, for the same patient, at different moments of time, the algorithm decides whether the hemangioma is evolvin…

0301 basic medicineMatching (graph theory)Computer sciencebusiness.industryFeature extractionFuzzy setMonitoring systemImage segmentationmedicine.diseaseFuzzy logicHemangioma03 medical and health sciences030104 developmental biologymedicineComputer visionArtificial intelligencebusiness2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)
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Full-automatic computer aided system for stem cell clustering using content-based microscopic image analysis

2017

Abstract Stem cells are very original cells that can differentiate into other cells, tissues and organs, which play a very important role in biomedical treatments. Because of the importance of stem cells, in this paper we propose a full-automatic computer aided clustering system to assist scientists to explore potential co-occurrence relations between the cell differentiation and their morphological information in phenotype. In this proposed system, a multi-stage Content-based Microscopic Image Analysis (CBMIA) framework is applied, including image segmentation, feature extraction, feature selection, feature fusion and clustering techniques. First, an Improved Supervised Normalized Cuts (IS…

0301 basic medicinebusiness.industryComputer scienceFeature extractionBiomedical EngineeringStability (learning theory)Pattern recognitionFeature selection02 engineering and technologyImage segmentation03 medical and health sciences030104 developmental biologyFeature (computer vision)Robustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSegmentationArtificial intelligencebusinessCluster analysisBiocybernetics and Biomedical Engineering
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