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matlab-based nuclear medicine data processing analysis tool  (MathWorks Inc)


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    MathWorks Inc matlab-based nuclear medicine data processing analysis tool
    Matlab Based Nuclear Medicine Data Processing Analysis Tool, 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/matlab-based+data+analysis+tool/pmc08217772-60-12-10
    Average 90 stars, based on 1 article reviews
    matlab-based nuclear medicine data processing analysis tool - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: High content, quantitative AFM analysis of the scalable biomechanical properties of extracellular vesicles.
    Article Snippet: AFM can retrieve accurate, quantitative data on sizing, geometry and biophysical properties, while the MATLAB-based data analysis tool provides the EV community with a tool for fast, efficient and standardised analysis of large, multi-signal AFM datasets commensurate with industry-scale production processes.



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    Image Search Results


    Multimodal setup in MEG environment. In the pictures, the black cables with fibre optics based sensors attached on the body and head are optical fibres for measurements of cNIBP and NIRS. On the right, shown is performing of simultaneous recording with the setup. During imaging, the display is used to instruct the subject to perform the given task.

    Journal: Scientific Reports

    Article Title: Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations

    doi: 10.1038/s41598-017-00293-7

    Figure Lengend Snippet: Multimodal setup in MEG environment. In the pictures, the black cables with fibre optics based sensors attached on the body and head are optical fibres for measurements of cNIBP and NIRS. On the right, shown is performing of simultaneous recording with the setup. During imaging, the display is used to instruct the subject to perform the given task.

    Article Snippet: Measured raw NIRS time courses were converted into two time courses representing temporal changes in HbO and Hb concentrations using Matlab-based NIRS data analysis tool HoMer2.

    Techniques: Imaging

    Comparison of mean power values (black dots, whiskers = SD) measured with magnetometers ( a ) and planar gradiometers ( b and c ), with (x axis) and without (y axis) the multimodal setup. For better visualisation the plots show an extract of all data, which were shown in each inset separately. In all cases the data can be well explained by a linear fit (red line). Note the slight positive intercept of the linear fits due to smaller power values when the multimodal setup is applied. The external sensors for NIRS are attached on back of the head and on forehead above left eye. Sensors for cNIBP are attached on chest and neck (see Figure ).

    Journal: Scientific Reports

    Article Title: Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations

    doi: 10.1038/s41598-017-00293-7

    Figure Lengend Snippet: Comparison of mean power values (black dots, whiskers = SD) measured with magnetometers ( a ) and planar gradiometers ( b and c ), with (x axis) and without (y axis) the multimodal setup. For better visualisation the plots show an extract of all data, which were shown in each inset separately. In all cases the data can be well explained by a linear fit (red line). Note the slight positive intercept of the linear fits due to smaller power values when the multimodal setup is applied. The external sensors for NIRS are attached on back of the head and on forehead above left eye. Sensors for cNIBP are attached on chest and neck (see Figure ).

    Article Snippet: Measured raw NIRS time courses were converted into two time courses representing temporal changes in HbO and Hb concentrations using Matlab-based NIRS data analysis tool HoMer2.

    Techniques: Comparison

    Averaged responses for PTT ( a ), BP ( b ), HR ( c ) measured with the cNIBP device; HbO/Hb ( d ) measured with the NIRS device from back of the head and four scouts (MEG) covering visual (green line), auditory (brown line), motor (dark yellow line) and temporal pole (blue line) brain areas ( e ). Average for NIRS and cNIBP data was calculated using values obtained during 4 breath holding sequences. Vertical bars represent standard deviation of the values. In addition, ( f ) shows an averaged response of 8 breath holds using the same breath hold task but recorded independently with our MREG multimodal setup . In all subfigures t = 0 marks the beginning of breath holding for 30 s, highlighted with grey area.

    Journal: Scientific Reports

    Article Title: Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations

    doi: 10.1038/s41598-017-00293-7

    Figure Lengend Snippet: Averaged responses for PTT ( a ), BP ( b ), HR ( c ) measured with the cNIBP device; HbO/Hb ( d ) measured with the NIRS device from back of the head and four scouts (MEG) covering visual (green line), auditory (brown line), motor (dark yellow line) and temporal pole (blue line) brain areas ( e ). Average for NIRS and cNIBP data was calculated using values obtained during 4 breath holding sequences. Vertical bars represent standard deviation of the values. In addition, ( f ) shows an averaged response of 8 breath holds using the same breath hold task but recorded independently with our MREG multimodal setup . In all subfigures t = 0 marks the beginning of breath holding for 30 s, highlighted with grey area.

    Article Snippet: Measured raw NIRS time courses were converted into two time courses representing temporal changes in HbO and Hb concentrations using Matlab-based NIRS data analysis tool HoMer2.

    Techniques: Standard Deviation