Search results for " fuzzy"

showing 10 items of 209 documents

Modelling the Effects of Internal Textures on Symmetry Detection Using Fuzzy Operators

2009

Symmetry is a crucial dimension which aids the visual system, human as well as artificial, to organize its environment and to recognize forms and objects. In humans, detection of symmetry, especially bilateral and rotational, is considered to be a primary factor for discovering and interacting with the surrounding environment. Rotational symmetry detecting can be affected by less-known factors, such as the stimulus internal texture. This paper explores how fuzzy operators can be usefully employed in modeling the effects of the internal texture on symmetry detection. To this aim, we selected two symmetry detection algorithms, based on different computational models, and compared their output…

Computational modelVisual perceptionSettore INF/01 - InformaticaComputer sciencebusiness.industryRotational symmetryFuzzy operatorsPattern recognitionFuzzy logicMemetic algorithmComputer visionArtificial intelligencebusinessvisual perception symmetry fuzzy logic
researchProduct

Automated prostate gland segmentation based on an unsupervised fuzzy C-means clustering technique using multispectral T1w and T2w MR imaging

2017

Prostate imaging analysis is difficult in diagnosis, therapy, and staging of prostate cancer. In clinical practice, Magnetic Resonance Imaging (MRI) is increasingly used thanks to its morphologic and functional capabilities. However, manual detection and delineation of prostate gland on multispectral MRI data is currently a time-expensive and operator-dependent procedure. Efficient computer-assisted segmentation approaches are not yet able to address these issues, but rather have the potential to do so. In this paper, a novel automatic prostate MR image segmentation method based on the Fuzzy C-Means (FCM) clustering algorithm, which enables multispectral T1-weighted (T1w) and T2-weighted (T…

Computer scienceAutomated segmentation; Fuzzy C-Means clustering; Multispectral MR imaging; Prostate cancer; Prostate gland; Unsupervised machine learningMultispectral image02 engineering and technologyautomated segmentation; multispectral MR imaging; prostate gland; prostate cancer; unsupervised Machine Learning; Fuzzy C-Means clustering030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer0302 clinical medicineProstate0202 electrical engineering electronic engineering information engineeringmedicineComputer visionSegmentationautomated segmentationunsupervised Machine LearningCluster analysisSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionimedicine.diagnostic_testbusiness.industryINF/01 - INFORMATICAMagnetic resonance imagingmedicine.diseaseprostate cancerFuzzy C-Means clusteringmultispectral MR imagingmedicine.anatomical_structureUnsupervised learning020201 artificial intelligence & image processingArtificial intelligencebusinessprostate glandInformation SystemsMultispectral segmentation
researchProduct

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
researchProduct

Exudates as Landmarks Identified through FCM Clustering in Retinal Images

2020

The aim of this work was to develop a method for the automatic identification of exudates, using an unsupervised clustering approach. The ability to classify each pixel as belonging to an eventual exudate, as a warning of disease, allows for the tracking of a patient&rsquo

Computer scienceDiabetic retinopathy; Exudates; Fuzzy C-means clustering; Morphological processing; Retinal landmarks; SegmentationFundus (eye)Fuzzy logiclcsh:TechnologyField (computer science)030218 nuclear medicine & medical imaginglcsh:Chemistry03 medical and health sciences0302 clinical medicineFcm clusteringfuzzy C-means clusteringretinal landmarksGeneral Materials ScienceSegmentationSensitivity (control systems)Cluster analysisInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer ProcessesSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPixelSettore INF/01 - Informaticabusiness.industrylcsh:TProcess Chemistry and TechnologyexudatessegmentationGeneral EngineeringPattern recognitionlcsh:QC1-999Computer Science Applicationsdiabetic retinopathyComputingMethodologies_PATTERNRECOGNITIONlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Artificial intelligencebusinesslcsh:Engineering (General). Civil engineering (General)030217 neurology & neurosurgerylcsh:Physicsmorphological processingApplied Sciences
researchProduct

Fully automatic multispectral MR image segmentation of prostate gland based on the fuzzy C-means clustering algorithm

2017

Prostate imaging is a very critical issue in the clinical practice, especially for diagnosis, therapy, and staging of prostate cancer. Magnetic Resonance Imaging (MRI) can provide both morphologic and complementary functional information of tumor region. Manual detection and segmentation of prostate gland and carcinoma on multispectral MRI data is not easily practicable in the clinical routine because of the long times required by experienced radiologists to analyze several types of imaging data. In this paper, a fully automatic image segmentation method, exploiting an unsupervised Fuzzy C-Means (FCM) clustering technique for multispectral T1-weighted and T2-weighted MRI data processing, is…

Computer scienceMultispectral imageFully automatic segmentation; Multispectral MR imaging; Prostate cancer; Prostate gland; Unsupervised fuzzy C-means clusteringFuzzy logic030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer0302 clinical medicineProstatemedicineSegmentationComputer visionCluster analysismedicine.diagnostic_testbusiness.industryINF/01 - INFORMATICAMagnetic resonance imagingfully automatic segmentationImage segmentationmedicine.diseaseprostate cancermultispectral MR imagingunsupervised Fuzzy C-Means clusteringmedicine.anatomical_structureArtificial intelligencebusinessprostate gland030217 neurology & neurosurgery
researchProduct

Fuzzy FMECA analysis of radioactive gas recovery system in the SPES experimental facility

2021

Abstract Selective Production of Exotic Species is an innovative plant for advanced nuclear physic studies. A radioactive beam, generated by using an UCx target-ion source system, is ionized, selected and accelerated for experimental objects. Very high vacuum conditions and appropriate safety systems to storage exhaust gases are required to avoid radiological risk for operators and people. In this paper, Failure Mode, Effects, and Criticality Analysis of a preliminary design of high activity gas recovery system is performed by using a modified Fuzzy Risk Priority Number to rank the most critical components in terms of failures and human errors. Comparisons between fuzzy approach and classic…

Computer scienceSPES FMECA Fuzzy Risk Priority Number evidence theory exhaust gas storage system020209 energySystem safety02 engineering and technologyFuzzy logicFuzzy risk priority numberPriority Number030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicine0202 electrical engineering electronic engineering information engineeringSettore ING-IND/19 - Impianti NucleariRank (computer programming)TK9001-9401SPESExhaust gas storage systemReliability engineeringEvidence theoryFailure mode effects and criticality analysisNuclear Energy and EngineeringNuclear engineering. Atomic powerRisk assessmentFailure mode and effects analysisRadioactive gasFMECANuclear Engineering and Technology
researchProduct

Three-dimensional Fuzzy Kernel Regression framework for registration of medical volume data

2013

Abstract In this work a general framework for non-rigid 3D medical image registration is presented. It relies on two pattern recognition techniques: kernel regression and fuzzy c-means clustering. The paper provides theoretic explanation, details the framework, and illustrates its application to implement three registration algorithms for CT/MR volumes as well as single 2D slices. The first two algorithms are landmark-based approaches, while the third one is an area-based technique. The last approach is based on iterative hierarchical volume subdivision, and maximization of mutual information. Moreover, a high performance Nvidia CUDA based implementation of the algorithm is presented. The f…

Computer sciencebusiness.industryImage registrationMutual informationMachine learningcomputer.software_genreFuzzy logicCUDANon-rigid registration Fuzzy regression Mutual information Interpolation GPU computingArtificial IntelligenceSignal ProcessingPattern recognition (psychology)Kernel regressionComputer Vision and Pattern RecognitionArtificial intelligenceData miningGeneral-purpose computing on graphics processing unitsCluster analysisbusinesscomputerSoftwareInterpolationPattern Recognition
researchProduct

Towards human cell simulation

2019

The faithful reproduction and accurate prediction of the phe-notypes and emergent behaviors of complex cellular systems are among the most challenging goals in Systems Biology. Although mathematical models that describe the interactions among all biochemical processes in a cell are theoretically feasible, their simulation is generally hard because of a variety of reasons. For instance, many quantitative data (e.g., kinetic rates) are usually not available, a problem that hinders the execution of simulation algorithms as long as some parameter estimation methods are used. Though, even with a candidate parameterization, the simulation of mechanistic models could be challenging due to the extr…

Constraint-based modelingAgent-based simulation; Big data; Biochemical simulation; Computational intelligence; Constraint-based modeling; Fuzzy logic; High-performance computing; Model reduction; Multi-scale modeling; Parameter estimation; Reaction-based modeling; Systems biology; Theoretical Computer Science; Computer Science (all)Computer scienceBiochemical simulationDistributed computingSystems biologyBig dataComputational intelligenceContext (language use)ING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONITheoretical Computer ScienceReduction (complexity)Big dataParameter estimationHigh-performance computingComputational intelligenceAgent-based simulationMathematical modelbusiness.industryModel reductionComputer Science (all)Multi-scale modelingINF/01 - INFORMATICASupercomputerVariety (cybernetics)Fuzzy logicReaction-based modelingbusinessSystems biology
researchProduct

Plastic or not plastic? That’s the problem: analysing the Italian students purchasing behavior of mineral water bottles made with eco-friendly packag…

2022

Abstract European Strategy for Plastics in a Circular Economy draws new shapes of economy in order to protect the environment and reduce marine pollution, GHGs and countries’ dependence on imported fossil fuels. The core of EU Strategy is also to try to transform the way plastic products are designed, produced, used and recycled in the EU. Italy is the first country in Europe and the second in the world for consumption of bottled water, with remarkable environmental impacts, from production to distribution. Starting from social science theory, this work aims to investigate consumers' behavior and the related factors that influence their behavior pertaining to the purchase of. mineral water …

Consumption (economics)Economics and EconometricsFuzzy clusterWater bottleFuzzy clusteringConsumer behaviour and sustainable consumptionCircular economyPlasticEnvironmental economicsBottled waterPurchasingSocial science theoryWork (electrical)Order (business)Settore AGR/01 - Economia Ed Estimo RuralePlastics; Social science theory; Water bottle; Consumer behaviour and sustainable consumption; Fuzzy clusteringGreen consumptionProduction (economics)BusinessWaste Management and DisposalResources, Conservation and Recycling
researchProduct

A BDI agent system for credit risk assessment based on fuzzy logic

2007

Credit risk has always been an important issue for banks and other financial intermediaries. A reliable and consistent computing system is necessary to simplify the decision making process in uncertain domains such as the assessment of credit risk. In recent years fuzzy logic techniques have been in their wide-ranging use in modeling of uncertainties, vagueness, impreciseness and the human thought process. Therefore in this paper we present a fuzzy logic based intelligent system for the assessment of credit risk. It aims at efficiently and intelligently managing the process, handling its complexity, and monitoring large amounts of dynamic information in a distributed way, by using a society…

Credit risk assessment Fuzzy logic Intelligent agents Practical reasoning
researchProduct