based nonlinear least square curve fitting algorithm lscurvefit routine using trust region reflective lm algorithm (MathWorks Inc)
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based nonlinear least square curve fitting algorithm lscurvefit routine using trust region reflective lm algorithm
Based Nonlinear Least Square Curve Fitting Algorithm Lscurvefit Routine Using Trust Region Reflective Lm 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
https://www.bioz.com/product/based+nonlinear+least+square+curve+fitting+algorithm+lscurvefit+routine+using+trust+region+reflective+lm+algorithm/pm32464580-92-1-1
Average 90 stars, based on 1 article reviews
Based Nonlinear Least Square Curve Fitting Algorithm Lscurvefit Routine Using Trust Region Reflective Lm 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
https://www.bioz.com/product/based+nonlinear+least+square+curve+fitting+algorithm+lscurvefit+routine+using+trust+region+reflective+lm+algorithm/pm32464580-92-1-1
Average 90 stars, based on 1 article reviews
based nonlinear least square curve fitting algorithm lscurvefit routine using trust region reflective lm algorithm - by Bioz Stars,
2026-09
90/100 stars
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other:Article Title: Evaluating feasibility of high resolution T1-perfusion MRI with whole brain coverage using compressed SENSE: Application to glioma grading. Article Snippet: Purpose: To evaluate the efficacy of optimized T1-Perfusion MRI protocol (protocol-2) with whole brain coverage and improved spatial resolution using Compressed-SENSE (CSENSE) to differentiate high-grade-glioma (HGG) and low-grade-glioma (LGG) and to compare it with the conventional protocol (protocol-1) with partial brain coverage used in our center.. Methods: This study included MRI data from 5 healthy volunteers, a phantom and 126 brain tumor patients.. Current study had two parts: To analyze the effect of CSENSE on 3D-T1-weighted (W) fast-field-echo (FFE) images, T1-W, dual-PDT2-W turbo-spin-echo images and T1 maps, and to evaluate the performance of high resolution T1-Perfusion MRI protocol with whole brain coverage optimized using CSENSE. |