Search results for "Volume segmentation"

showing 2 items of 2 documents

3D segmentation of abdominal aorta from CT-scan and MR images

2012

International audience; We designed a generic method for segmenting the aneurismal sac of an abdominal aortic aneurysm (AAA) both from multi-slice MR and CT-scan examinations. It is a semi-automatic method requiring little human intervention and based on graph cut theory to segment the lumen interface and the aortic wall of AAAs. Our segmentation method works independently on MRI and CT-scan volumes and has been tested on a 44 patient dataset and 10 synthetic images. Segmentation and maximum diameter estimation were compared to manual tracing from 4 experts. An inter-observer study was performed in order to measure the variability range of a human observer. Based on three metrics (the maxim…

CT scanmedicine.medical_specialty[INFO.INFO-IM] Computer Science [cs]/Medical ImagingLumen (anatomy)Health Informatics02 engineering and technologyAAA segmentationPattern Recognition Automated030218 nuclear medicine & medical imaging03 medical and health sciencesAortic aneurysmImaging Three-Dimensional0302 clinical medicineCutmedicine.arteryImage Interpretation Computer-Assisted[INFO.INFO-IM]Computer Science [cs]/Medical Imaging0202 electrical engineering electronic engineering information engineeringmedicineHumansRadiology Nuclear Medicine and imagingSegmentationMathematicsAnalysis of VarianceRadiological and Ultrasound Technology[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingVolume segmentationAbdominal aortaReproducibility of Resultsmedicine.diseaseComputer Graphics and Computer-Aided DesignAbdominal aortic aneurysmHausdorff distancecardiovascular system020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionTomographyRadiologyTomography X-Ray ComputedAlgorithmsMagnetic Resonance AngiographyGraph cutAortic Aneurysm AbdominalMRI
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Active contour algorithm with discriminant analysis for delineating tumors in positron emission tomography.

2019

Abstract In the context of cancer delineation using positron emission tomography datasets, we present an innovative approach which purpose is to tackle the real-time, three-dimensional segmentation task in a full, or at least nearly full automatized way. The approach comprises a preliminary initialization phase where the user highlights a region of interest around the cancer on just one slice of the tomographic dataset. The algorithm takes care of identifying an optimal and user-independent region of interest around the anomalous tissue and located on the slice containing the highest standardized uptake value so to start the successive segmentation task. The three-dimensional volume is then…

Positron emission tomographyComputer scienceInitializationMedicine (miscellaneous)Context (language use)Imaging phantomActive contour algorithm03 medical and health sciences0302 clinical medicineRegion of interestArtificial IntelligenceNeoplasmsmedicineHumansSegmentation030304 developmental biologyRetrospective Studies0303 health sciencesActive contour modelDiscriminant analysimedicine.diagnostic_testbusiness.industryDiscriminant AnalysisPattern recognitionLinear discriminant analysisPositron emission tomographyBiological target volume segmentationPositron-Emission TomographyArtificial intelligencebusiness030217 neurology & neurosurgeryAlgorithmsArtificial intelligence in medicine
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