Search results for "Brain image segmentation"

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Hidden Markov random field model and Broyden–Fletcher–Goldfarb–Shanno algorithm for brain image segmentation

2018

International audience; Many routine medical examinations produce images of patients suffering from various pathologies. With the huge number of medical images, the manual analysis and interpretation became a tedious task. Thus, automatic image segmentation became essential for diagnosis assistance. Segmentation consists in dividing the image into homogeneous and significant regions. We focus on hidden Markov random fields referred to as HMRF to model the problem of segmentation. This modelisation leads to a classical function minimisation problem. Broyden-Fletcher-Goldfarb-Shanno algorithm referred to as BFGS is one of the most powerful methods to solve unconstrained optimisation problem. …

Dice coefficient criterionComputer scienceBrain image segmentation02 engineering and technologyMR-images[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Theoretical Computer Science03 medical and health sciences0302 clinical medicineArtificial Intelligence0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]SegmentationBrain magnetic resonance imagingHidden Markov modelRandom fieldbusiness.industryBroyden-Fletcher-Goldfarb-Shanno algorithmPattern recognitionImage segmentationhidden Markov random fieldMinimization3. Good healthHomogeneousBroyden–Fletcher–Goldfarb–Shanno algorithm020201 artificial intelligence & image processingAutomatic segmentationArtificial intelligenceHidden Markov random fieldbusiness030217 neurology & neurosurgerySoftwareJournal of Experimental & Theoretical Artificial Intelligence
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Conjugate Gradient Method for Brain Magnetic Resonance Images Segmentation

2018

Part 8: Pattern Recognition and Image Processing; International audience; Image segmentation is the process of partitioning the image into regions of interest in order to provide a meaningful representation of information. Nowadays, segmentation has become a necessity in many practical medical imaging methods as locating tumors and diseases. Hidden Markov Random Field model is one of several techniques used in image segmentation. It provides an elegant way to model the segmentation process. This modeling leads to the minimization of an objective function. Conjugate Gradient algorithm (CG) is one of the best known optimization techniques. This paper proposes the use of the nonlinear Conjugat…

Ground truthComputer sciencebusiness.industryThe Conjugate Gradient algorithmComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONBrain image segmentationPattern recognition02 engineering and technologyImage segmentationImage (mathematics)Nonlinear conjugate gradient method03 medical and health sciences0302 clinical medicineDice Coefficient metricHidden Markov Random FieldConjugate gradient methodComputer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSegmentation[INFO]Computer Science [cs]Artificial intelligencebusinessHidden Markov random field030217 neurology & neurosurgery
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