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dce-mri data processing  (MathWorks Inc)


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    MathWorks Inc dce-mri data processing
    Dce Mri Data Processing, 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/dce-mri+data+processing/pmc03102848-71-0-7
    Average 90 stars, based on 1 article reviews
    dce-mri data processing - by Bioz Stars, 2026-10
    90/100 stars

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    other:

    Article Title: Changes in hippocampal volume during a preceding 10-year period do not correlate with cognitive performance and hippocampal blood‒brain barrier permeability in cognitively normal late-middle-aged men
    Article Snippet: The DCE MRI data were analysed with a semiautomated procedure using in-house developed MATLAB (MathWorks, Natick, MA, USA) software, as previously described [ ].

    Article Title: Implementation of Oxygen Enhanced Magnetic Resonance Imaging (OE-MRI) and a Pilot Genomic Study of Hypoxia in Bladder Cancer Xenografts
    Article Snippet: DCE-MRI (OE-MRI) images were analysed using MATLAB ® version R2017a.

    Article Title: Assessment of Hepatocellular Carcinoma Response to 90 Y Radioembolization Using Dynamic Contrast Material–enhanced MRI and Intravoxel Incoherent Motion Diffusion-weighted Imaging
    Article Snippet: Additional histogram parameters (central tendency parameter median and heterogeneity parameters [standard deviation, kurtosis, and skewness]) of the DCE MRI and IVIM DWI parameters in the lesion ROIs at baseline were extracted using MATLAB built-in functions.


    Article Title: Glioma Type Prediction with Dynamic Contrast-Enhanced MR Imaging and Diffusion Kurtosis Imaging—A Standardized Multicenter Study
    Article Snippet: The values of the following DCE-MRI and DWI parameters were calculated using scripts written in MATLAB (R2018b (The MathWorks, Inc., Natick, MA, USA; http://www.mathworks.com )) accessed on 2 June 2024: Apparent diffusion coefficient (ADC), mean kurtosis (MK), Ktrans, Kep, vp, ve, cerebral blood volume (CBV), time to peak (TTP), peak, area under the curve (AUC DCE ), wash in, and wash out.

    Article Title: Predicting of axillary lymph node metastasis in invasive breast cancer using multiparametric MRI dataset based on CNN model
    Article Snippet: We later used Matlab-R2018b (Math works, Massachusetts, USA) software to crop out the ROI from T2WI, DWI, and DCE-MRI raw images of 252 breast cancer, and the ROI segmentation example is in .

    Article Title: 3D anatomical and perfusion MRI for longitudinal evaluation of biomaterials for bone regeneration of femoral bone defect in rats
    Article Snippet: The analyses of the DCE-MRI were performed on a pixel-wise basis using the Matlab software (Mathworks Inc., France).

    Software:

    Article Title: Radiation-Induced Changes in Tumor Vessels and Microenvironment Contribute to Therapeutic Resistance in Glioblastoma.
    Article Snippet: .. For DCE-MRI, we applied semi-quantitative analysis using a home-made routine in Matlab (R2013a) software (Mathworks, Inc.). .. Briefly, a T1 mapping was obtained with VNMRI (Agilent Technologies, Santa Clara, CA, USA).



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    In vivo rVDI and rVSI maps and quantitative curves for tumor xenografts of CL1-0 cancer cells overexpressing one of three VEGF isoforms, evaluated by <t>SSCE-MRI.</t> Representative high-resolution maps of the (A) rVDI and (B) rVSI in the different VEGF-overexpressing and mock tumors on day 36 after tumor implantation. In rVDI map, the color ranged from blue (0 S -1/3 , lowest rVDI) to red (0.4 S -1/3 , highest rVDI). In rVSI map, the color ranged from blue (0, lowest rVSI) to red (30, highest rVSI).Quantitative analysis of (C) rVDI and (D) rVSI in the whole tumor (upper), tumor rim (middle), or tumor core (lower). Differences between VEGF-overexpressing tumors and mock tumors were significant at the * p <0.05, ** p <0.01, *** p <0.001, and **** p <0.0001 levels.
    The Processing Software For All Of The Quantitative Analyses Of The Data Obtained By Dce And Ssce Mri, 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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    dce-mri data processing  (MathWorks Inc)
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    MathWorks Inc dce-mri data processing
    In vivo rVDI and rVSI maps and quantitative curves for tumor xenografts of CL1-0 cancer cells overexpressing one of three VEGF isoforms, evaluated by <t>SSCE-MRI.</t> Representative high-resolution maps of the (A) rVDI and (B) rVSI in the different VEGF-overexpressing and mock tumors on day 36 after tumor implantation. In rVDI map, the color ranged from blue (0 S -1/3 , lowest rVDI) to red (0.4 S -1/3 , highest rVDI). In rVSI map, the color ranged from blue (0, lowest rVSI) to red (30, highest rVSI).Quantitative analysis of (C) rVDI and (D) rVSI in the whole tumor (upper), tumor rim (middle), or tumor core (lower). Differences between VEGF-overexpressing tumors and mock tumors were significant at the * p <0.05, ** p <0.01, *** p <0.001, and **** p <0.0001 levels.
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    dce-mri data processing - by Bioz Stars, 2026-10
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    In vivo rVDI and rVSI maps and quantitative curves for tumor xenografts of CL1-0 cancer cells overexpressing one of three VEGF isoforms, evaluated by SSCE-MRI. Representative high-resolution maps of the (A) rVDI and (B) rVSI in the different VEGF-overexpressing and mock tumors on day 36 after tumor implantation. In rVDI map, the color ranged from blue (0 S -1/3 , lowest rVDI) to red (0.4 S -1/3 , highest rVDI). In rVSI map, the color ranged from blue (0, lowest rVSI) to red (30, highest rVSI).Quantitative analysis of (C) rVDI and (D) rVSI in the whole tumor (upper), tumor rim (middle), or tumor core (lower). Differences between VEGF-overexpressing tumors and mock tumors were significant at the * p <0.05, ** p <0.01, *** p <0.001, and **** p <0.0001 levels.

    Journal: PLoS ONE

    Article Title: Functional and Structural Characteristics of Tumor Angiogenesis in Lung Cancers Overexpressing Different VEGF Isoforms Assessed by DCE- and SSCE-MRI

    doi: 10.1371/journal.pone.0016062

    Figure Lengend Snippet: In vivo rVDI and rVSI maps and quantitative curves for tumor xenografts of CL1-0 cancer cells overexpressing one of three VEGF isoforms, evaluated by SSCE-MRI. Representative high-resolution maps of the (A) rVDI and (B) rVSI in the different VEGF-overexpressing and mock tumors on day 36 after tumor implantation. In rVDI map, the color ranged from blue (0 S -1/3 , lowest rVDI) to red (0.4 S -1/3 , highest rVDI). In rVSI map, the color ranged from blue (0, lowest rVSI) to red (30, highest rVSI).Quantitative analysis of (C) rVDI and (D) rVSI in the whole tumor (upper), tumor rim (middle), or tumor core (lower). Differences between VEGF-overexpressing tumors and mock tumors were significant at the * p <0.05, ** p <0.01, *** p <0.001, and **** p <0.0001 levels.

    Article Snippet: The processing software for all of the quantitative analyses of the data obtained by DCE- and SSCE-MRI was written in MATLAB (MathWorks, Natick, MA, USA).

    Techniques: In Vivo, Tumor Implantation