Search results for "unsupervised clustering"

showing 3 items of 3 documents

Gamma Knife treatment planning: MR brain tumor segmentation and volume measurement based on unsupervised Fuzzy C-Means clustering

2015

Nowadays, radiation treatment is beginning to intensively use MRI thanks to its greater ability to discriminate healthy and diseased soft-tissues. Leksell Gamma Knife® is a radio-surgical device, used to treat different brain lesions, which are often inaccessible for conventional surgery, such as benign or malignant tumors. Currently, the target to be treated with radiation therapy is contoured with slice-by-slice manual segmentation on MR datasets. This approach makes the segmentation procedure time consuming and operator-dependent. The repeatability of the tumor boundary delineation may be ensured only by using automatic or semiautomatic methods, supporting clinicians in the treatment pla…

Jaccard indexSimilarity (geometry)Computer scienceScale-space segmentationFuzzy logicunsupervised clusteringmagnetic resonance imagingSegmentationComputer visionmagnetic resonance imag- ingElectrical and Electronic EngineeringCluster analysisRadiation treatment planningSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPixelbrain tumors; Gamma Knife treatment planning; magnetic resonance imaging; semi-automatic segmentation; unsupervised clusteringbusiness.industrybrain tumors Gamma Knife treatment planning magnetic resonance imaging semi-automatic segmentation unsupervised clusteringElectronic Optical and Magnetic Materialsbrain tumorsComputer Vision and Pattern RecognitionArtificial intelligencebusinesssemi-automatic segmentationSoftwarebrain tumorGamma Knife treatment planning
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Screen media and non-screen media habits among preschool children in Singapore, South Korea, Japan, and Finland: Insights from an unsupervised cluste…

2021

The main purpose of the research was to describe the daily screen media habits and non-screen media habits like indoor and outdoor play, and sleep of preschool children aged 2 to 6 years from Singapore, South Korea, Japan, and Finland using a content-validated online questionnaire (SMALLQ®) and unsupervised cluster analysis. Unsupervised cluster analysis on 5809 parent-reported weekday and weekend screen and non-screen media habits of preschool children from the four countries resulted in seven emergent clusters. Cluster 2 ( n = 1288) or the Early-screen media, screen media-lite and moderate-to-vigorous physical activity-lite family made up 22.2% and Cluster 1 ( n = 261) or the High-all-ro…

Singaporepreschool childrenmediankäyttöHealth PolicyruutuaikaHealth Informaticsunsupervised clusteringComputer Science ApplicationsesikouluJapanHealth Information ManagementSouth KoreaesikouluikäisetelämäntapaFinlandlifestyle habitsDigital health
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Unsupervised clustering method for pattern recognition in IIF images

2017

Autoimmune diseases are a family of more than 80 chronic, and often disabling, illnesses that develop when underlying defects in the immune system lead the body to attack its own organs, tissues, and cells. Diagnosis of autoimmune pathologies is based on research and identification of antinuclear antibodies (ANA) through indirect immunofluorescence (IIF) method and is performed by analyzing patterns and fluorescence intensity. We propose here a method to automatically classify the centromere pattern based on the grouping of centromeres on the cells through a clustering K-means algorithm. The described method was tested on a public database (MIVIA). The results of the test showed an Accuracy…

business.industryPattern recognitionIIfBiologyIIF imageSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)K-meanIdentification (information)Fluorescence intensityStatistical classificationPattern recognitionPattern recognition (psychology)Autoimmune diseaseAutomatic segmentationArtificial intelligenceUnsupervised clusteringCluster analysisbusinessclustering
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