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motion compensated diffusion sequence  (Philips Healthcare)

 
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    Structured Review

    Philips Healthcare motion compensated diffusion sequence
    Schematic diagram of the analytical procedure for <t>the</t> <t>motion‐compensated</t> diffusion imaging with phase‐contrast (MC‐DIP). (A) Data acquisition: Diffusion‐weighted imaging (DWI) with multiple b ‐values is acquired using three gradient schemes (2nd‐MC, 1st‐MC, and non‐MC), along with phase‐contrast (PC) MRI of the internal carotid arteries (ICAs) and vertebral arteries (VAs). (B) Biexponential diffusion analysis: The DWI data are processed using a stepwise biexponential fitting to estimate the true diffusion coefficient ( D ), perfusion‐related diffusion coefficient ( D *), and perfusion fraction ( F ), from which a relative perfusion map ( FD *) is calculated. (C) Absolute regional cerebral blood flow (rCBF) calculation: The PC‐MRI data are used to calculate total cerebral blood flow (tCBF). A conversion factor is determined by dividing tCBF by the whole‐brain sum of FD * values. The final absolute rCBF map is then generated by multiplying the FD * map by this conversion factor.
    Motion Compensated Diffusion Sequence, supplied by Philips Healthcare, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/motion+compensated+diffusion+sequence/pmc13156429-158-1-11?v=Philips+Healthcare
    Average 86 stars, based on 1 article reviews
    motion compensated diffusion sequence - by Bioz Stars, 2026-07
    86/100 stars

    Images

    1) Product Images from "Motion‐Compensated Diffusion Imaging With Phase‐Contrast for Robust Quantification of Regional Cerebral Blood Flow"

    Article Title: Motion‐Compensated Diffusion Imaging With Phase‐Contrast for Robust Quantification of Regional Cerebral Blood Flow

    Journal: Magnetic Resonance in Medicine

    doi: 10.1002/mrm.70324

    Schematic diagram of the analytical procedure for the motion‐compensated diffusion imaging with phase‐contrast (MC‐DIP). (A) Data acquisition: Diffusion‐weighted imaging (DWI) with multiple b ‐values is acquired using three gradient schemes (2nd‐MC, 1st‐MC, and non‐MC), along with phase‐contrast (PC) MRI of the internal carotid arteries (ICAs) and vertebral arteries (VAs). (B) Biexponential diffusion analysis: The DWI data are processed using a stepwise biexponential fitting to estimate the true diffusion coefficient ( D ), perfusion‐related diffusion coefficient ( D *), and perfusion fraction ( F ), from which a relative perfusion map ( FD *) is calculated. (C) Absolute regional cerebral blood flow (rCBF) calculation: The PC‐MRI data are used to calculate total cerebral blood flow (tCBF). A conversion factor is determined by dividing tCBF by the whole‐brain sum of FD * values. The final absolute rCBF map is then generated by multiplying the FD * map by this conversion factor.
    Figure Legend Snippet: Schematic diagram of the analytical procedure for the motion‐compensated diffusion imaging with phase‐contrast (MC‐DIP). (A) Data acquisition: Diffusion‐weighted imaging (DWI) with multiple b ‐values is acquired using three gradient schemes (2nd‐MC, 1st‐MC, and non‐MC), along with phase‐contrast (PC) MRI of the internal carotid arteries (ICAs) and vertebral arteries (VAs). (B) Biexponential diffusion analysis: The DWI data are processed using a stepwise biexponential fitting to estimate the true diffusion coefficient ( D ), perfusion‐related diffusion coefficient ( D *), and perfusion fraction ( F ), from which a relative perfusion map ( FD *) is calculated. (C) Absolute regional cerebral blood flow (rCBF) calculation: The PC‐MRI data are used to calculate total cerebral blood flow (tCBF). A conversion factor is determined by dividing tCBF by the whole‐brain sum of FD * values. The final absolute rCBF map is then generated by multiplying the FD * map by this conversion factor.

    Techniques Used: Diffusion-based Assay, Imaging, Generated

    Representative rCBF maps from a single subject obtained using the three different DIP schemes and the reference ASL method. The non‐MC‐DIP shows prominent artifacts (areas of artificially high signal, red). These artifacts are partially reduced with 1st‐MC and most effectively suppressed with 2nd‐MC, resulting in maps with spatial distribution and contrast comparable to the ASL reference. rCBF, regional cerebral blood flow; MC‐DIP, motion‐compensated diffusion imaging with phase‐contrast; ASL, arterial spin labeling.
    Figure Legend Snippet: Representative rCBF maps from a single subject obtained using the three different DIP schemes and the reference ASL method. The non‐MC‐DIP shows prominent artifacts (areas of artificially high signal, red). These artifacts are partially reduced with 1st‐MC and most effectively suppressed with 2nd‐MC, resulting in maps with spatial distribution and contrast comparable to the ASL reference. rCBF, regional cerebral blood flow; MC‐DIP, motion‐compensated diffusion imaging with phase‐contrast; ASL, arterial spin labeling.

    Techniques Used: Diffusion-based Assay, Imaging, Labeling

    Comparison of biexponential fitting accuracy, as measured by the normalized root mean squared error (nRMSE), for (A) gray matter (GM) and (B) white matter (WM). The boxplots compare the second‐order motion‐compensated (2nd‐MC), first‐order motion‐compensated (1st‐MC), and non‐compensated (non‐MC) schemes. In GM, both the 1st‐MC and 2nd‐MC schemes were superior to the non‐MC scheme. In WM, however, only the 2nd‐MC scheme significantly reduced the fitting error compared with both other methods.
    Figure Legend Snippet: Comparison of biexponential fitting accuracy, as measured by the normalized root mean squared error (nRMSE), for (A) gray matter (GM) and (B) white matter (WM). The boxplots compare the second‐order motion‐compensated (2nd‐MC), first‐order motion‐compensated (1st‐MC), and non‐compensated (non‐MC) schemes. In GM, both the 1st‐MC and 2nd‐MC schemes were superior to the non‐MC scheme. In WM, however, only the 2nd‐MC scheme significantly reduced the fitting error compared with both other methods.

    Techniques Used: Comparison

    Scatter plots showing the correlation between DIP‐ and ASL‐derived rCBF in gray matter (GM; top row, A–C) and white matter (WM; bottom row, D–F). Each data point represents the mean rCBF value for each subject ( n = 11). The plots correspond to the second‐order motion‐compensated (2nd‐MC; A, D), first‐order motion‐compensated (1st‐MC; B, E), and non‐compensated (non‐MC; C, F) schemes. Spearman's correlation coefficients ( ρ ) and p values are shown. While all schemes correlated with ASL in GM, only the 2nd‐MC scheme established a significant correlation in WM. DIP, diffusion imaging with phase‐contrast; ASL, arterial spin labeling; rCBF, regional cerebral blood flow.
    Figure Legend Snippet: Scatter plots showing the correlation between DIP‐ and ASL‐derived rCBF in gray matter (GM; top row, A–C) and white matter (WM; bottom row, D–F). Each data point represents the mean rCBF value for each subject ( n = 11). The plots correspond to the second‐order motion‐compensated (2nd‐MC; A, D), first‐order motion‐compensated (1st‐MC; B, E), and non‐compensated (non‐MC; C, F) schemes. Spearman's correlation coefficients ( ρ ) and p values are shown. While all schemes correlated with ASL in GM, only the 2nd‐MC scheme established a significant correlation in WM. DIP, diffusion imaging with phase‐contrast; ASL, arterial spin labeling; rCBF, regional cerebral blood flow.

    Techniques Used: Derivative Assay, Diffusion-based Assay, Imaging, Labeling



    Similar Products

    motion compensated diffusion sequence  (Philips Healthcare)
    86
    Philips Healthcare motion compensated diffusion sequence
    Schematic diagram of the analytical procedure for <t>the</t> <t>motion‐compensated</t> diffusion imaging with phase‐contrast (MC‐DIP). (A) Data acquisition: Diffusion‐weighted imaging (DWI) with multiple b ‐values is acquired using three gradient schemes (2nd‐MC, 1st‐MC, and non‐MC), along with phase‐contrast (PC) MRI of the internal carotid arteries (ICAs) and vertebral arteries (VAs). (B) Biexponential diffusion analysis: The DWI data are processed using a stepwise biexponential fitting to estimate the true diffusion coefficient ( D ), perfusion‐related diffusion coefficient ( D *), and perfusion fraction ( F ), from which a relative perfusion map ( FD *) is calculated. (C) Absolute regional cerebral blood flow (rCBF) calculation: The PC‐MRI data are used to calculate total cerebral blood flow (tCBF). A conversion factor is determined by dividing tCBF by the whole‐brain sum of FD * values. The final absolute rCBF map is then generated by multiplying the FD * map by this conversion factor.
    Motion Compensated Diffusion Sequence, supplied by Philips Healthcare, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/motion+compensated+diffusion+sequence/pmc13156429-158-1-11?v=Philips+Healthcare
    Average 86 stars, based on 1 article reviews
    motion compensated diffusion sequence - by Bioz Stars, 2026-07
    86/100 stars
    		  Buy from Supplier

    Image Search Results


    Schematic diagram of the analytical procedure for the motion‐compensated diffusion imaging with phase‐contrast (MC‐DIP). (A) Data acquisition: Diffusion‐weighted imaging (DWI) with multiple b ‐values is acquired using three gradient schemes (2nd‐MC, 1st‐MC, and non‐MC), along with phase‐contrast (PC) MRI of the internal carotid arteries (ICAs) and vertebral arteries (VAs). (B) Biexponential diffusion analysis: The DWI data are processed using a stepwise biexponential fitting to estimate the true diffusion coefficient ( D ), perfusion‐related diffusion coefficient ( D *), and perfusion fraction ( F ), from which a relative perfusion map ( FD *) is calculated. (C) Absolute regional cerebral blood flow (rCBF) calculation: The PC‐MRI data are used to calculate total cerebral blood flow (tCBF). A conversion factor is determined by dividing tCBF by the whole‐brain sum of FD * values. The final absolute rCBF map is then generated by multiplying the FD * map by this conversion factor.

    Journal: Magnetic Resonance in Medicine

    Article Title: Motion‐Compensated Diffusion Imaging With Phase‐Contrast for Robust Quantification of Regional Cerebral Blood Flow

    doi: 10.1002/mrm.70324

    Figure Lengend Snippet: Schematic diagram of the analytical procedure for the motion‐compensated diffusion imaging with phase‐contrast (MC‐DIP). (A) Data acquisition: Diffusion‐weighted imaging (DWI) with multiple b ‐values is acquired using three gradient schemes (2nd‐MC, 1st‐MC, and non‐MC), along with phase‐contrast (PC) MRI of the internal carotid arteries (ICAs) and vertebral arteries (VAs). (B) Biexponential diffusion analysis: The DWI data are processed using a stepwise biexponential fitting to estimate the true diffusion coefficient ( D ), perfusion‐related diffusion coefficient ( D *), and perfusion fraction ( F ), from which a relative perfusion map ( FD *) is calculated. (C) Absolute regional cerebral blood flow (rCBF) calculation: The PC‐MRI data are used to calculate total cerebral blood flow (tCBF). A conversion factor is determined by dividing tCBF by the whole‐brain sum of FD * values. The final absolute rCBF map is then generated by multiplying the FD * map by this conversion factor.

    Article Snippet: The motion‐compensated diffusion sequence used in this research was provided by Philips as part of a research agreement.

    Techniques: Diffusion-based Assay, Imaging, Generated

    Representative rCBF maps from a single subject obtained using the three different DIP schemes and the reference ASL method. The non‐MC‐DIP shows prominent artifacts (areas of artificially high signal, red). These artifacts are partially reduced with 1st‐MC and most effectively suppressed with 2nd‐MC, resulting in maps with spatial distribution and contrast comparable to the ASL reference. rCBF, regional cerebral blood flow; MC‐DIP, motion‐compensated diffusion imaging with phase‐contrast; ASL, arterial spin labeling.

    Journal: Magnetic Resonance in Medicine

    Article Title: Motion‐Compensated Diffusion Imaging With Phase‐Contrast for Robust Quantification of Regional Cerebral Blood Flow

    doi: 10.1002/mrm.70324

    Figure Lengend Snippet: Representative rCBF maps from a single subject obtained using the three different DIP schemes and the reference ASL method. The non‐MC‐DIP shows prominent artifacts (areas of artificially high signal, red). These artifacts are partially reduced with 1st‐MC and most effectively suppressed with 2nd‐MC, resulting in maps with spatial distribution and contrast comparable to the ASL reference. rCBF, regional cerebral blood flow; MC‐DIP, motion‐compensated diffusion imaging with phase‐contrast; ASL, arterial spin labeling.

    Article Snippet: The motion‐compensated diffusion sequence used in this research was provided by Philips as part of a research agreement.

    Techniques: Diffusion-based Assay, Imaging, Labeling

    Comparison of biexponential fitting accuracy, as measured by the normalized root mean squared error (nRMSE), for (A) gray matter (GM) and (B) white matter (WM). The boxplots compare the second‐order motion‐compensated (2nd‐MC), first‐order motion‐compensated (1st‐MC), and non‐compensated (non‐MC) schemes. In GM, both the 1st‐MC and 2nd‐MC schemes were superior to the non‐MC scheme. In WM, however, only the 2nd‐MC scheme significantly reduced the fitting error compared with both other methods.

    Journal: Magnetic Resonance in Medicine

    Article Title: Motion‐Compensated Diffusion Imaging With Phase‐Contrast for Robust Quantification of Regional Cerebral Blood Flow

    doi: 10.1002/mrm.70324

    Figure Lengend Snippet: Comparison of biexponential fitting accuracy, as measured by the normalized root mean squared error (nRMSE), for (A) gray matter (GM) and (B) white matter (WM). The boxplots compare the second‐order motion‐compensated (2nd‐MC), first‐order motion‐compensated (1st‐MC), and non‐compensated (non‐MC) schemes. In GM, both the 1st‐MC and 2nd‐MC schemes were superior to the non‐MC scheme. In WM, however, only the 2nd‐MC scheme significantly reduced the fitting error compared with both other methods.

    Article Snippet: The motion‐compensated diffusion sequence used in this research was provided by Philips as part of a research agreement.

    Techniques: Comparison

    Scatter plots showing the correlation between DIP‐ and ASL‐derived rCBF in gray matter (GM; top row, A–C) and white matter (WM; bottom row, D–F). Each data point represents the mean rCBF value for each subject ( n = 11). The plots correspond to the second‐order motion‐compensated (2nd‐MC; A, D), first‐order motion‐compensated (1st‐MC; B, E), and non‐compensated (non‐MC; C, F) schemes. Spearman's correlation coefficients ( ρ ) and p values are shown. While all schemes correlated with ASL in GM, only the 2nd‐MC scheme established a significant correlation in WM. DIP, diffusion imaging with phase‐contrast; ASL, arterial spin labeling; rCBF, regional cerebral blood flow.

    Journal: Magnetic Resonance in Medicine

    Article Title: Motion‐Compensated Diffusion Imaging With Phase‐Contrast for Robust Quantification of Regional Cerebral Blood Flow

    doi: 10.1002/mrm.70324

    Figure Lengend Snippet: Scatter plots showing the correlation between DIP‐ and ASL‐derived rCBF in gray matter (GM; top row, A–C) and white matter (WM; bottom row, D–F). Each data point represents the mean rCBF value for each subject ( n = 11). The plots correspond to the second‐order motion‐compensated (2nd‐MC; A, D), first‐order motion‐compensated (1st‐MC; B, E), and non‐compensated (non‐MC; C, F) schemes. Spearman's correlation coefficients ( ρ ) and p values are shown. While all schemes correlated with ASL in GM, only the 2nd‐MC scheme established a significant correlation in WM. DIP, diffusion imaging with phase‐contrast; ASL, arterial spin labeling; rCBF, regional cerebral blood flow.

    Article Snippet: The motion‐compensated diffusion sequence used in this research was provided by Philips as part of a research agreement.

    Techniques: Derivative Assay, Diffusion-based Assay, Imaging, Labeling