Search results for " fuzzy c-means"

showing 2 items of 12 documents

A fully automatic 2D segmentation method for uterine fibroid in MRgFUS treatment evaluation

2015

PurposeMagnetic Resonance guided Focused UltraSound (MRgFUS) represents a non-invasive surgical approach that uses thermal ablation to treat uterine fibroids. After the MRgFUS treatment, an operator must manually segment the treated fibroid areas to evaluate the NonPerfused Volume (NPV). This manual approach is operator-dependent, introducing issues of result reproducibility, which could lead to errors in the subsequent follow-up phase. Moreover, manual segmentation is time-consuming, and can have a negative impact on the optimization of both machine-time and operator-time. MethodTo address these issues, in this paper a novel fully automatic method based on the unsupervised Fuzzy C-Means cl…

medicine.medical_specialtyDatabases FactualUterine fibroidsComputer scienceAdaptive thresholdingImage ProcessingAdaptive thresholding; Automatic segmentation; Fuzzy C-Means clustering; MRgFUS treatment; Uterine fibroids; Female; Humans; Image Processing Computer-Assisted; Leiomyoma; Radiography; Algorithms; Databases Factual; Magnetic Resonance Imaging; Ultrasonography InterventionalHealth InformaticsFuzzy logicDatabasesComputer-AssistedImage Processing Computer-AssistedmedicineHumansSegmentationCluster analysisFactualUltrasonography InterventionalUltrasonographySettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInterventionalLeiomyomaPixelbusiness.industryPattern recognitionmedicine.diseaseMagnetic Resonance ImagingFuzzy C-Means clusteringComputer Science ApplicationsSurgeryRadiographyTreatment evaluationMRgFUS treatmentFully automaticFemaleManual segmentationArtificial intelligenceAutomatic segmentationAdaptive thresholding Automatic segmentation Fuzzy C-Means clustering MRgFUS treatment Uterine fibroidsbusinessAlgorithmsUterine fibroids
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NeXt for neuro-radiosurgery: A fully automatic approach for necrosis extraction in brain tumor MRI using an unsupervised machine learning technique

2017

Stereotactic neuro-radiosurgery is a well-established therapy for intracranial diseases, especially brain metastases and highly invasive cancers that are difficult to treat with conventional surgery or radiotherapy. Nowadays, magnetic resonance imaging (MRI) is the most used modality in radiation therapy for soft-tissue anatomical districts, allowing for an accurate gross tumor volume (GTV) segmentation. Investigating also necrotic material within the whole tumor has significant clinical value in treatment planning and cancer progression assessment. These pathological necrotic regions are generally characterized by hypoxia, which is implicated in several aspects of tumor development and gro…

medicine.medical_specialtyPathologyING-INF/06 - BIOINGEGNERIA ELETTRONICA E INFORMATICAmedicine.medical_treatmentunsupervisedFuzzy C-Means clusteringBrain tumorRadiosurgeryING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI030218 nuclear medicine & medical imaging03 medical and health sciencesnecrosis extraction0302 clinical medicineMagnetic resonance imagingmedicineSegmentationElectrical and Electronic EngineeringRadiation treatment planningmedicine.diagnostic_testSettore INF/01 - Informaticabusiness.industryneuro-radiosurgery treatmentsNeuro-radiosurgery treatmentbrain tumors; magnetic resonance imaging; necrosis extraction; neuro-radiosurgery treatments; unsupervisedFuzzy C-Means clustering;brain tumors; magnetic resonance imaging; necrosis extraction; neuro-radiosurgery treatments; unsupervised Fuzzy C-Means clusteringCancerINF/01 - INFORMATICAMagnetic resonance imagingmedicine.diseaseElectronic Optical and Magnetic MaterialsRadiation therapyunsupervised Fuzzy C-Means clusteringBrain tumorUnsupervised learningbrain tumorsComputer Vision and Pattern RecognitionRadiologybusiness030217 neurology & neurosurgerySoftware
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