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Medviso AB segment 2.0
Segment 2.0, supplied by Medviso AB, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/matlab-based+data+analysis+scripts/segment+2+0/pmc06298529-108-12-17
Average 90 stars, based on 1 article reviews
segment 2.0 - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Prognostic value of biventricular mechanical parameters assessed using cardiac magnetic resonance feature-tracking analysis to predict future cardiac events.
Article Snippet: Purpose: To study and compare the prognostic value of cardiac magnetic resonance feature tracking (MR-FT) of biventricular strain parameters with a conventional method.. Materials and Methods: We retrospectively enrolled 364 patients undergoing clinically indicated cardiac MR examinations (1.5 or 3T scanner).. Standard steady-state free precession (SSFP) images were used for analysis.

Article Title: Characterization of acute TLR-7 agonist-induced hemorrhagic myocarditis in mice by multiparametric quantitative cardiac magnetic resonance imaging
Article Snippet: Data analysis was performed using Segment 2.0 (Segment, Medviso).

Article Title: Bulk Flow and Near Wall Hemodynamics of the Rabbit Aortic Arch and Descending Thoracic Aorta: A 4D PC-MRI Derived Computational Fluid Dynamics Study
Article Snippet: A semi-automatic level set approach was used for image segmentation using the matlab -based program (Segment 2.0, Medviso, Lund, Sweden) [ 19 , 20 ].

Article Title: Detection of acute TLR-7 agonist-induced hemorrhagic myocarditis in mice by refined multi-parametric quantitative cardiac MRI
Article Snippet: A pixel wise T 2 * mono-exponential fit was performed on the multiple echo T 2 * w-UTE images using Segment 2.0 (Segment, Medviso) ( ).

Article Title: Characterization of acute TLR-7 agonist-induced hemorrhagic myocarditis in mice by multiparametric quantitative cardiac magnetic resonance imaging
Article Snippet: A pixelwise T 2 * mono-exponential fit was performed on the multiple echo T 2 * w-UTE images using Segment 2.0 (Segment, Medviso) ( , ).



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