Search results for "Region growing"

showing 3 items of 23 documents

Automatic detection of lung nodules in CT datasets based on stable 3D mass–spring models

2012

We propose a computer-aided detection (CAD) system which can detect small-sized (from 3 mm) pulmonary nodules in spiral CT scans. A pulmonary nodule is a small lesion in the lungs, round-shaped (parenchymal nodule) or worm-shaped (juxtapleural nodule). Both kinds of lesions have a radio-density greater than lung parenchyma, thus appearing white on the images. Lung nodules might indicate a lung cancer and their early stage detection arguably improves the patient survival rate. CT is considered to be the most accurate imaging modality for nodule detection. However, the large amount of data per examination makes the full analysis difficult, leading to omission of nodules by the radiologist. We…

medicine.medical_specialtyLung NeoplasmsDatabases FactualHealth InformaticsCADModels BiologicalSensitivity and SpecificityImaging Three-DimensionalSegmentationLung nodulemedicineFalse positive paradoxSegmentation; Lung nodules; Active contours models;Computer tomography (CT); Mass–spring models; Spline curves; Image featuresHumansSegmentationDiagnosis Computer-AssistedStage (cooking)Lung cancerComputer tomography (CT)business.industryNodule (medicine)Image featuresSpline curvemedicine.diseaseSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Computer Science ApplicationsRegion growingMass–spring modelRadiologyTomographymedicine.symptombusinessTomography Spiral ComputedAlgorithmsActive contours model
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A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model

2007

A computer-aided detection (CAD) system for the selection of lung nodules in computer tomography (CT) images is presented. The system is based on region growing (RG) algorithms and a new active contour model (ACM), implementing a local convex hull, able to draw the correct contour of the lung parenchyma and to include the pleural nodules. The CAD consists of three steps: (1) the lung parenchymal volume is segmented by means of a RG algorithm; the pleural nodules are included through the new ACM technique; (2) a RG algorithm is iteratively applied to the previously segmented volume in order to detect the candidate nodules; (3) a double-threshold cut and a neural network are applied to reduce…

medicine.medical_specialtyLung NeoplasmsRadiation DosageModels BiologicalEdge detectionImage processingMedical imagingmedicineHumansDiagnosis Computer-AssistedComputed radiographycomputer-aided diagnosis (CAD)Lungimage segmentationComputed tomographyActive contour modelImage segmentationbusiness.industrycomputed tomographyGeneral MedicineImage segmentationComputer-aided diagnosis (CAD)image processingROC CurveRegion growingComputer-aided diagnosisRadiologyTomographyNeural Networks Computercomputer-aided diagnosis (CAD)image processingcomputed tomographyimage segmentationNuclear medicinebusinessTomography X-Ray ComputedAlgorithms
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Automatic dynamic texture segmentation using local descriptors and optical flow

2012

A dynamic texture (DT) is an extension of the texture to the temporal domain. How to segment a DT is a challenging problem. In this paper, we address the problem of segmenting a DT into disjoint regions. A DT might be different from its spatial mode (i.e., appearance) and/or temporal mode (i.e., motion field). To this end, we develop a framework based on the appearance and motion modes. For the appearance mode, we use a new local spatial texture descriptor to describe the spatial mode of the DT; for the motion mode, we use the optical flow and the local temporal texture descriptor to represent the temporal variations of the DT. In addition, for the optical flow, we use the histogram of orie…

ta113business.industrySegmentation-based object categorizationComputer scienceTexture DescriptorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowScale-space segmentationPattern recognitionImage segmentationComputer Graphics and Computer-Aided DesignImage textureMotion fieldRegion growingComputer Science::Computer Vision and Pattern RecognitionHistogramComputer visionSegmentationArtificial intelligencebusinessSoftwareIEEE Transactions on Image Processing
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