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mri data  (Philips Healthcare)

 
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    Philips Healthcare mri data
    Mri Data, 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/mri+data/mri+scanner+t/pm41933844-66-1-7
    Average 86 stars, based on 1 article reviews
    mri data - by Bioz Stars, 2026-10
    86/100 stars

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    Related Articles

    Magnetic Resonance Imaging:

    Article Title: Deep Learning to Differentiate Parkinsonian Syndromes Using Multimodal Magnetic Resonance Imaging: A Proof-of-Concept Study.
    Article Snippet: .. MRI data were acquired in each participant center using 3T MRI scanners (Siemens Healthineers, Erlangen, Germany for Paris, Philips Achieva dsTream , Best, the Netherlands for Toulouse, and GE Discovery MR750, Chicago, Illinois, United States for Bordeaux). ..

    Article Title: Individual gray-white matter functional connection predicts tau spread and cognitive decline in Alzheimer's disease.
    Article Snippet: .. The MRI data were acquired with a Philips or Siemens 3.0T scanner. ..

    Article Title: Multimodal brain structural and functional analysis in systemic lupus erythematosus patients without overt neuropsychiatric manifestations: associations with disease duration, organ damage, and neurocognitive function.
    Article Snippet: .. MRI data was obtained using a 3 Tesla Philips Ingenia magnetic resonance imaging scanner (Philips Medical Systems Nederland B.V., Eindhoven, Netherlands) located in Chungbuk National University Hospital. ..

    Article Title: Deep Learning to Differentiate Parkinsonian Syndromes Using Multimodal Magnetic Resonance Imaging : A Proof‐of‐Concept Study
    Article Snippet: .. MRI data were acquired in each participant center using 3T MRI scanners (Siemens Healthineers, Erlangen, Germany for Paris, Philips Achieva dsTream, Best, the Netherlands for Toulouse, and GE Discovery MR750, Chicago, Illinois, United States for Bordeaux). ..

    Article Title: Do enlarged white matter perivascular spaces reflect brain clearance dysfunction? Insights from intrathecal contrast-enhanced MRI.
    Article Snippet: .. Slice orientation of image stacks was defined using an automated anatomy recognition protocol based on landmark detection in MRI data (SmartExamTM, Philips Medical Systems, Best, The Netherlands) for each time point to secure consistency and reproducibility of the MRI slice placement and orientation. ..

    Article Title: Association of APOC1 with cortical atrophy during conversion to Alzheimer's disease.
    Article Snippet: .. Image acquisition MRI data from ADNI were scanned using Philips Medical Systems, Siemens Medical Solutions, and GE Healthcare 3 T scanners. .. T1-weighted (T1w) images were acquired with a three-dimensional (3D) magnetization-prepared rapid acquisition gradient echo sequence for Philips and Siemens medical systems scanners (Philips: repetition time [TR] = 6.8 ms, echo time [TE] = 3.2 ms, and flip angle = 9°; Siemens: TR = 2300 ms; TE = 2.98 ms, flip angle = 9°).

    Article Title: MRI annotation using an inversion-based preprocessing for CT model adaptation
    Article Snippet: .. CT scans and MRI data were acquired using scanners from Siemens, Philips, General Electric, and Toshiba. ..



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    Workflow for the detection of disclination lines. (a) Bar plot representation of the fibre orientation field within the myocardium based on <t>MRI</t> <t>data.</t> Each bar indicates the local fibre direction derived from diffusion tensor imaging. (b-d) Computational pipeline for detecting disclination lines. The cleaning procedure removes artefactual features that do not represent topologically significant disclinations, including: boundary-related fluctuations near tissue surfaces, poorly resolved regions of the right ventricle (RV) where the wall thickness is too thin, and small surface loops that can be trivially resolved. (b) Frobenius norm of the disclination density tensor throughout the myocardium, showing fibre orientational disorder. (c) Extracted cores of regions where the Frobenius norm exhibits significantly large values, identifying potential singular sites. (d) Final result after the cleaning procedure, displaying only the disclination lines that are topologically relevant for cardiac fibre organisation.
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    Workflow for the detection of disclination lines. (a) Bar plot representation of the fibre orientation field within the myocardium based on <t>MRI</t> <t>data.</t> Each bar indicates the local fibre direction derived from diffusion tensor imaging. (b-d) Computational pipeline for detecting disclination lines. The cleaning procedure removes artefactual features that do not represent topologically significant disclinations, including: boundary-related fluctuations near tissue surfaces, poorly resolved regions of the right ventricle (RV) where the wall thickness is too thin, and small surface loops that can be trivially resolved. (b) Frobenius norm of the disclination density tensor throughout the myocardium, showing fibre orientational disorder. (c) Extracted cores of regions where the Frobenius norm exhibits significantly large values, identifying potential singular sites. (d) Final result after the cleaning procedure, displaying only the disclination lines that are topologically relevant for cardiac fibre organisation.
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    Workflow for the detection of disclination lines. (a) Bar plot representation of the fibre orientation field within the myocardium based on <t>MRI</t> <t>data.</t> Each bar indicates the local fibre direction derived from diffusion tensor imaging. (b-d) Computational pipeline for detecting disclination lines. The cleaning procedure removes artefactual features that do not represent topologically significant disclinations, including: boundary-related fluctuations near tissue surfaces, poorly resolved regions of the right ventricle (RV) where the wall thickness is too thin, and small surface loops that can be trivially resolved. (b) Frobenius norm of the disclination density tensor throughout the myocardium, showing fibre orientational disorder. (c) Extracted cores of regions where the Frobenius norm exhibits significantly large values, identifying potential singular sites. (d) Final result after the cleaning procedure, displaying only the disclination lines that are topologically relevant for cardiac fibre organisation.
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    Workflow for the detection of disclination lines. (a) Bar plot representation of the fibre orientation field within the myocardium based on <t>MRI</t> <t>data.</t> Each bar indicates the local fibre direction derived from diffusion tensor imaging. (b-d) Computational pipeline for detecting disclination lines. The cleaning procedure removes artefactual features that do not represent topologically significant disclinations, including: boundary-related fluctuations near tissue surfaces, poorly resolved regions of the right ventricle (RV) where the wall thickness is too thin, and small surface loops that can be trivially resolved. (b) Frobenius norm of the disclination density tensor throughout the myocardium, showing fibre orientational disorder. (c) Extracted cores of regions where the Frobenius norm exhibits significantly large values, identifying potential singular sites. (d) Final result after the cleaning procedure, displaying only the disclination lines that are topologically relevant for cardiac fibre organisation.
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    heart cartesian 4d flow mri data  (Philips Healthcare)
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    Examples of <t>4D</t> Flow <t>MRI</t> reference magnitude and velocity images (first column) for data from Site A. For each row, columns 2–6 show the differences between the reference and images reconstructed with models trained on 1–5 (Training Set 1–5 respectively) datasets. Note that there are no apparent systematic differences due to the size of the training set.
    Heart Cartesian 4d Flow Mri Data, 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
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    Image Search Results


    Workflow for the detection of disclination lines. (a) Bar plot representation of the fibre orientation field within the myocardium based on MRI data. Each bar indicates the local fibre direction derived from diffusion tensor imaging. (b-d) Computational pipeline for detecting disclination lines. The cleaning procedure removes artefactual features that do not represent topologically significant disclinations, including: boundary-related fluctuations near tissue surfaces, poorly resolved regions of the right ventricle (RV) where the wall thickness is too thin, and small surface loops that can be trivially resolved. (b) Frobenius norm of the disclination density tensor throughout the myocardium, showing fibre orientational disorder. (c) Extracted cores of regions where the Frobenius norm exhibits significantly large values, identifying potential singular sites. (d) Final result after the cleaning procedure, displaying only the disclination lines that are topologically relevant for cardiac fibre organisation.

    Journal: bioRxiv

    Article Title: Topological defects and coherent myocardial chirality shape torsional heart contraction

    doi: 10.64898/2026.04.13.718243

    Figure Lengend Snippet: Workflow for the detection of disclination lines. (a) Bar plot representation of the fibre orientation field within the myocardium based on MRI data. Each bar indicates the local fibre direction derived from diffusion tensor imaging. (b-d) Computational pipeline for detecting disclination lines. The cleaning procedure removes artefactual features that do not represent topologically significant disclinations, including: boundary-related fluctuations near tissue surfaces, poorly resolved regions of the right ventricle (RV) where the wall thickness is too thin, and small surface loops that can be trivially resolved. (b) Frobenius norm of the disclination density tensor throughout the myocardium, showing fibre orientational disorder. (c) Extracted cores of regions where the Frobenius norm exhibits significantly large values, identifying potential singular sites. (d) Final result after the cleaning procedure, displaying only the disclination lines that are topologically relevant for cardiac fibre organisation.

    Article Snippet: Cardiac geometry was extracted from microscopy images or MRI data using Imaris software (Bitplane, version 10.0.0) to isolate the shape of the myocardium.

    Techniques: Derivative Assay, Diffusion-based Assay, Imaging

    Examples of 4D Flow MRI reference magnitude and velocity images (first column) for data from Site A. For each row, columns 2–6 show the differences between the reference and images reconstructed with models trained on 1–5 (Training Set 1–5 respectively) datasets. Note that there are no apparent systematic differences due to the size of the training set.

    Journal: Magnetic Resonance in Medicine

    Article Title: FlowVN Trained on a Single Dataset Enables Rapid Reconstruction of Highly Accelerated 4D Flow MRI Across Multiple Sites

    doi: 10.1002/mrm.70317

    Figure Lengend Snippet: Examples of 4D Flow MRI reference magnitude and velocity images (first column) for data from Site A. For each row, columns 2–6 show the differences between the reference and images reconstructed with models trained on 1–5 (Training Set 1–5 respectively) datasets. Note that there are no apparent systematic differences due to the size of the training set.

    Article Snippet: Fully‐sampled whole‐heart cartesian 4D flow MRI data were acquired at our institution (referred to as Site A) using a Philips 1.5 T Achieva scanner (Philips Healthcare, Best, The Netherlands) with software version 5.7.1, in 16 healthy volunteers during free breathing.

    Techniques: