Search results for "Accurate segmentation"

showing 3 items of 3 documents

GridNet with Automatic Shape Prior Registration for Automatic MRI Cardiac Segmentation

2018

In this paper, we propose a fully automatic MRI cardiac segmentation method based on a novel deep convolutional neural network (CNN) designed for the 2017 ACDC MICCAI challenge. The novelty of our network comes with its embedded shape prior and its loss function tailored to the cardiac anatomy. Our model includes a cardiac center-of-mass regression module which allows for an automatic shape prior registration. Also, since our method processes raw MR images without any manual preprocessing and/or image cropping, our CNN learns both high-level features (useful to distinguish the heart from other organs with a similar shape) and low-level features (useful to get accurate segmentation results).…

Cardiac anatomybusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONNovelty030204 cardiovascular system & hematologyGridConvolutional neural networkAccurate segmentation030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineFully automaticPreprocessorSegmentationComputer visionArtificial intelligencebusiness
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Towards a unified analysis of brain maturation and aging across the entire lifespan: A MRI analysis

2017

Previous literature about the structural characterization of the human cerebellum is related to the context of a specific pathology or focused in a restricted age range. In fact, studies about the cerebellum maturation across the lifespan are scarce and most of them considered the cerebellum as a whole without investigating each lobule. This lack of study can be explained by the lack of both accurate segmentation methods and data availability. Fortunately, during the last years, several cerebellum segmentation methods have been developed and many databases comprising subjects of different ages have been made publically available. This fact opens an opportunity window to obtain a more extens…

CerebellumRadiological and Ultrasound TechnologyCerebellum maturation05 social sciencesBrain maturationContext (language use)Degeneration (medical)Slow growth050105 experimental psychologyAccurate segmentation03 medical and health sciences0302 clinical medicinemedicine.anatomical_structureNeurologymedicine0501 psychology and cognitive sciencesRadiology Nuclear Medicine and imagingSegmentationNeurology (clinical)AnatomyPsychologyNeuroscience030217 neurology & neurosurgeryHuman Brain Mapping
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A deep semantic segmentation-based algorithm to segment crops and weeds in agronomic color images

2022

Abstract In precision agriculture, the accurate segmentation of crops and weeds in agronomic images has always been the center of attention. Many methods have been proposed but still the clean and sharp segmentation of crops and weeds is a challenging issue for the images with a high presence of weeds. This work proposes a segmentation method based on the combination of semantic segmentation and K-means algorithms for the segmentation of crops and weeds in color images. Agronomic images of two different databases were used for the segmentation algorithms. Using the thresholding technique, everything except plants was removed from the images. Afterward, semantic segmentation was applied usin…

Subtractive colorComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONConfusion matrixForestryAquatic ScienceThresholdingAccurate segmentationComputer Science ApplicationsClassification rateAnimal Science and ZoologySegmentationPrecision agricultureCluster analysisAgronomy and Crop ScienceAlgorithmInformation Processing in Agriculture
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