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Partial volume correction (PVC)

PVC

Partial Volume Correction


Partial Volume Correction modifies volume-of-interest statistics in order to compensate the Partial Volume Effect. It ensures the proper quantification of objects taking into account spill-over and spill-in between regions.

 

Recovery-Coefficients-Method


The Recovery Coefficients Method corrects the volume-of-interest measurement using a correction factor based on the volume. A reference table with these factors for different volumes is used and interpolated for the specific correction factor to be applied. Different sets of recovery coefficients can be specified in a configuration file and then be selected within the application.

Geometric-Transfer-Matrix-Method


The Geometric Transfer Matrix Method calculates recovery and crosscontamination factors of volumes-of-interest in the image. These geometry-dependent transfer coefficients form a matrix representing the fraction of true activity from each volume-of-interest observed in any other volume-of-interest. This matrix can be inverted to correct for Partial Volume Effects, independent of the tracer concentrations in each volume-of-interest.

Lucy-Richardson-Deconvolution


Lucy-Richardson Deconvolution estimates a corrected image first and then evaluates the volume-of-interest on the corrected image. The corrected image is estimated in an iterative fashion starting with the acquired image.
It takes into account the point-spread-function of the imaging system as well.

Blind-Deconvolution


Blind Deconvolution is an extension of the Lucy-Richardson Deconvolution where both the corrected and the point-spread-function (PSF) are estimated. The volume-of-interest is evaluated on the corrected image as for Lucy-Richardson. The corrected image and the PSF are estimated in an iterative fashion starting with the acquired image and initial PSF.

  • Selection of volumes-of-interest for the computation of the partial volume correction

  • Output table showing the corrected statistics for the selected volumes of interest

  • Image based partial volume correction using the Lucy-Richardson algorithm as a prerequisite for accurate lesion quantification

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Images

  • Selection of volumes-of-interest for the computation of the partial volume correction

    Selection of volumes-of-interest for the computation of the partial volume correction

  • Output table showing the corrected statistics for the selected volumes of interest

    Output table showing the corrected statistics for the selected volumes of interest

  • Image based partial volume correction using the Lucy-Richardson algorithm as a prerequisite for accurate lesion quantification

    Image based partial volume correction using the Lucy-Richardson algorithm as a prerequisite for accurate lesion quantification

  • Selection of volumes-of-interest for the computation of the partial volume correction

    Selection of volumes-of-interest for the computation of the partial volume correction

  • Output table showing the corrected statistics for the selected volumes of interest

    Output table showing the corrected statistics for the selected volumes of interest

  • Image based partial volume correction using the Lucy-Richardson algorithm as a prerequisite for accurate lesion quantification

    Image based partial volume correction using the Lucy-Richardson algorithm as a prerequisite for accurate lesion quantification

Selection of volumes-of-interest for the computation of the partial volume correction
Output table showing the corrected statistics for the selected volumes of interest
Image based partial volume correction using the Lucy-Richardson algorithm as a prerequisite for accurate lesion quantification
Caution: Imalytics and its modules are for research purposes only. Not for patient diagnosis or patient treatment planning.