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Related Concept Videos

Magnetic Resonance Imaging01:24

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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
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A pulse is a short burst of radio waves distributed over a range of frequencies that simultaneously excites all the nuclei in the sample. Upon passing a radio frequency pulse along the x-axis, the nuclei absorb energy corresponding to their Larmor frequencies and achieve resonance. This shifts the net magnetization vector from the z-axis toward the transverse plane. This angle of rotation of the magnetization vector, or the flip angle, is proportional to the duration and intensity of the pulse.
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Fast analytical spectral filtering methods for magnetic resonance perfusion quantification.

Kasireddy V Reddy, Abhishek Mitra, Phaneendra K Yalavarthy

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 9, 2017
    PubMed
    Summary

    Two novel deconvolution methods for perfusion weighted imaging (PWI) offer faster and more accurate quantification of MR perfusion parameters in stroke and brain tumor studies compared to existing techniques.

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    Area of Science:

    • Medical Imaging
    • Neuroscience
    • Biophysics

    Background:

    • Perfusion weighted imaging (PWI) is crucial for quantifying MR perfusion parameters.
    • PWI is standard clinical practice for stroke and brain tumor assessment.
    • Current deconvolution methods like oSVD and FDD have limitations.

    Purpose of the Study:

    • To develop and evaluate novel, fast deconvolution methods for PWI.
    • To improve computational efficiency and quantitative accuracy in MR perfusion analysis.

    Main Methods:

    • Proposed two analytical deconvolution methods: analytical Fourier filtering and analytical Showalter spectral filtering.
    • Systematically evaluated the performance of the proposed methods against standard FDD and oSVD.

    Main Results:

    • The proposed methods demonstrated superior computational efficiency.
    • Quantitative accuracy of the novel methods was comparable or superior to FDD and oSVD.
    • These findings suggest potential for faster and more precise PWI analysis.

    Conclusions:

    • The developed analytical deconvolution techniques offer a promising advancement for PWI.
    • These methods can enhance the speed and accuracy of MR perfusion parameter quantification.
    • Potential for improved clinical applications in neuroimaging, particularly for stroke and tumors.