The purpose of this HIPAA-compliant, institutional review board-approved study was to assess the liver and spleen volumes calculated by using a semiautomated dual-space clustering segmentation technique, as compared with the volumes calculated by using the manual contour-tracing method. The quantitative magnetic resonance (MR) imaging data used as input were computed from images acquired by using a mixed fast spin-echo pulse sequence that was implemented with respiratory triggering. Linear regression analysis was used to assess agreement regarding the volumes calculated by using both segmentation techniques. There was strong agreement regarding the regression parameters for the liver (r = 0.98, P < .001) and the spleen (r = 0.99, P < .001) and the mean percentage volume differences for the liver (1.2%) and the spleen (0.9%). The mean segmentation time per patient was significantly shorter with use of the dual-space clustering method (P < .001).
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http://dx.doi.org/10.1148/radiol.2371041416 | DOI Listing |
Front Plant Sci
June 2023
College of Mechanical and Electrical Engineering, Shihezi University, Shihezi, China.
Accurate road extraction and recognition of roadside fruit in complex orchard environments are essential prerequisites for robotic fruit picking and walking behavioral decisions. In this study, a novel algorithm was proposed for unstructured road extraction and roadside fruit synchronous recognition, with wine grapes and nonstructural orchards as research objects. Initially, a preprocessing method tailored to field orchards was proposed to reduce the interference of adverse factors in the operating environment.
View Article and Find Full Text PDFIEEE Trans Vis Comput Graph
July 2023
In this paper, we present TeethGNN, a novel 3D tooth segmentation method based on graph neural networks (GNNs). Given a mesh-represented 3D dental model in non-euclidean domain, our method outputs accurate and fine-grained separation of each individual tooth robust to scanning noise, foreign matters (e.g.
View Article and Find Full Text PDFPLoS One
June 2016
Centre for Advanced Spatial Analysis(CASA), University College London, London, United Kingdom.
The success or failure of the street network depends on its reliability. In this article, using resilience analysis, the author studies how the shape and appearance of street networks in self-organised and top-down planned cities influences urban transport. Considering London and Beijing as proxies for self-organised and top-down planned cities, the structural properties of London and Beijing networks first are investigated based on their primal and dual representations of planar graphs.
View Article and Find Full Text PDFMagn Reson Imaging
September 2006
Boston University Medical Center, Boston University, Boston, MA 02118, USA.
The combined T1, T2 and secular-T2 pixel frequency distributions of 24 adult human brains were studied in vivo using a technique based on the mixed-TSE pulse sequence, dual-space clustering segmentation and histogram gaussian decomposition. Pixel frequency histograms of whole brains and the four principal brain compartments were studied comparatively and as function of age. For white matter, the position of the T1 peak correlates with age (R2 =.
View Article and Find Full Text PDFRadiology
October 2005
Department of Radiology, Boston Medical Center and Boston University School of Medicine, 88 E Newton St, Radiology Suite, Second Floor, Boston, MA 02118, USA.
The purpose of this HIPAA-compliant, institutional review board-approved study was to assess the liver and spleen volumes calculated by using a semiautomated dual-space clustering segmentation technique, as compared with the volumes calculated by using the manual contour-tracing method. The quantitative magnetic resonance (MR) imaging data used as input were computed from images acquired by using a mixed fast spin-echo pulse sequence that was implemented with respiratory triggering. Linear regression analysis was used to assess agreement regarding the volumes calculated by using both segmentation techniques.
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