Search results for "Adaptive thresholding"

showing 3 items of 3 documents

A Robust Multi Stage Technique for Image Binarization of Degraded Historical Documents

2017

International audience; Document image binarization is a central problem in many document analysis systems. Indeed, it represents one of the basic challenges, especially in case of historical documents analysis. In this paper, we propose a novel robust multi stage framework that combines different existing document image thresholding methods for the purpose of getting a better binarization result. CLAHE technique is introduced to significantly enhance contrast in some poor images. The proposed method then uses a hybrid algorithm to partition image into foreground and background. A special procedure is finally applied in order to remove small noise and correct characters morphology. Experime…

adaptive thresholdingComputer scienceHistorical document image analysis[SPI] Engineering Sciences [physics]ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyhybrid algorithm01 natural sciencesGrayscaleElectronic mail010309 optics[SPI]Engineering Sciences [physics]Histogram0103 physical sciences0202 electrical engineering electronic engineering information engineeringNoise measurementbusiness.industryPattern recognitionImage segmentationglobal thresholdingThresholding[SPI.TRON] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsComputingMethodologies_DOCUMENTANDTEXTPROCESSINGcontrast enhancement020201 artificial intelligence & image processingAlgorithm designAdaptive histogram equalizationArtificial intelligencebusiness
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A novel framework for MR image segmentation and quantification by using MedGA

2019

BACKGROUND AND OBJECTIVES: Image segmentation represents one of the most challenging issues in medical image analysis to distinguish among different adjacent tissues in a body part. In this context, appropriate image pre-processing tools can improve the result accuracy achieved by computer-assisted segmentation methods. Taking into consideration images with a bimodal intensity distribution, image binarization can be used to classify the input pictorial data into two classes, given a threshold intensity value. Unfortunately, adaptive thresholding techniques for two-class segmentation work properly only for images characterized by bimodal histograms. We aim at overcoming these limitations and…

ING-INF/06 - BIOINGEGNERIA ELETTRONICA E INFORMATICAAdaptive thresholding; Bimodal intensity distribution; Evolutionary computation; Image pre-processing; Magnetic Resonance imaging; Quantitative medical imagingComputer scienceAdaptive thresholdingImage ProcessingDecision MakingNeurosurgeryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHealth InformaticsContext (language use)Adaptive thresholding; Bimodal intensity distribution; Evolutionary computation; Image pre-processing; Magnetic Resonance imaging; Quantitative medical imaging; Algorithms; Brain Neoplasms; Computer Simulation; Decision Making; Female; Humans; Image Processing Computer-Assisted; Leiomyoma; Neurosurgery; Radiosurgery; Software; Magnetic Resonance ImagingEvolutionary computationRadiosurgeryING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI030218 nuclear medicine & medical imaging03 medical and health sciencesComputer-Assisted0302 clinical medicineHistogramQuantitative medical imagingmedicineImage Processing Computer-AssistedHumansSegmentationComputer SimulationHistogram equalizationmedicine.diagnostic_testLeiomyomaSettore INF/01 - Informaticabusiness.industryBrain NeoplasmsINF/01 - INFORMATICAMagnetic resonance imagingPattern recognitionImage segmentationThresholdingComputer Science ApplicationsBimodal intensity distributionImage pre-processingTransformation (function)Magnetic Resonance imagingFemaleArtificial intelligencebusiness030217 neurology & neurosurgeryAlgorithmsSoftware
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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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