linear regression function mldivide Search Results


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A flowchart depicting the MRI post-processing procedure used in this work. Step 1, the field map (fB) was estimated from the complex multi-echo data using a 2D graphcut algorithm. Step 2, R2* was estimated using the previously estimated field map from step 1 and a variable projection algorithm. Step 3, using the field map and R2* estimations from steps 1 and 2, the decomposition parameters (ρW, ρF, ndb, nmidb, and cl) were determined by solving the adapted 6- or 9-peak linear system of equations using the <t>mldivide</t> algorithm. Finally, PDFF was estimated using the already estimated ρW and ρF maps. The necessary a priori spectral model information for each algorithm is given below its name.
Mldivide Algorithm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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A flowchart depicting the MRI post-processing procedure used in this work. Step 1, the field map (fB) was estimated from the complex multi-echo data using a 2D graphcut algorithm. Step 2, R2* was estimated using the previously estimated field map from step 1 and a variable projection algorithm. Step 3, using the field map and R2* estimations from steps 1 and 2, the decomposition parameters (ρW, ρF, ndb, nmidb, and cl) were determined by solving the adapted 6- or 9-peak linear system of equations using the <t>mldivide</t> algorithm. Finally, PDFF was estimated using the already estimated ρW and ρF maps. The necessary a priori spectral model information for each algorithm is given below its name.
Mldivide ('\), supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


A flowchart depicting the MRI post-processing procedure used in this work. Step 1, the field map (fB) was estimated from the complex multi-echo data using a 2D graphcut algorithm. Step 2, R2* was estimated using the previously estimated field map from step 1 and a variable projection algorithm. Step 3, using the field map and R2* estimations from steps 1 and 2, the decomposition parameters (ρW, ρF, ndb, nmidb, and cl) were determined by solving the adapted 6- or 9-peak linear system of equations using the mldivide algorithm. Finally, PDFF was estimated using the already estimated ρW and ρF maps. The necessary a priori spectral model information for each algorithm is given below its name.

Journal: Magnetic resonance imaging

Article Title: Fat spectral modeling on triglyceride composition quantification using chemical shift encoded magnetic resonance imaging

doi: 10.1016/j.mri.2018.06.012

Figure Lengend Snippet: A flowchart depicting the MRI post-processing procedure used in this work. Step 1, the field map (fB) was estimated from the complex multi-echo data using a 2D graphcut algorithm. Step 2, R2* was estimated using the previously estimated field map from step 1 and a variable projection algorithm. Step 3, using the field map and R2* estimations from steps 1 and 2, the decomposition parameters (ρW, ρF, ndb, nmidb, and cl) were determined by solving the adapted 6- or 9-peak linear system of equations using the mldivide algorithm. Finally, PDFF was estimated using the already estimated ρW and ρF maps. The necessary a priori spectral model information for each algorithm is given below its name.

Article Snippet: Using the previously estimated f B and R 2 * maps within an adapted 6- or 9-peak linear system of equations, estimates of the decomposition parameters (ρ W , ρ F , ndb , nmidb , and cl ) were determined on a voxel by voxel basis using the mldivide algorithm provided by Matlab to find the linear least-squares solution.

Techniques: