Method for assessing and/or reducing artifacts arising from reconstruction of MPI image data and system for visual representation of MPI image data
A method for assessing and/or reducing artifacts arising from reconstruction of magnetic particle imaging (MPI) total image data set (c(r)) from MPI signal data (s(f), u(t)) using an appended system matrix (SM_AB) comprises: a) reconstructing signal data (s(f), u(t)) using appended system matrix (SM_AB) derived from at least two system matrices (SM_A, SM_B) for generating input image data (cin(r)); b) selecting at least one voxel as selected voxel from the input image data (cin(r)) for generating output image data (cout(r)); c) determining eigen-reconstruction signal data se n (f) by selecting one or more line entries of the appended system matrix (SM_AB) that correspond to the selected voxel(s); d) reconstructing eigen-reconstruction signal data se(f) using the appended system matrix (SM_AB) for generating eigen-reconstruction image data ce(r); and e) subtracting the eigen-reconstruction image data ce(r) or weighted eigen-reconstruction image data ce′(r) from the input image data cin(r) for generating updated input image data cin n ′(r).
1 . A method for reducing artifacts arising from reconstruction of a magnetic particle imaging (MPI) total image data set (c(r)) from MPI signal data, the method comprising:
a1) providing MPI signal data (s(f), u(t)) acquired from a sample using an MPI apparatus;
a2) reconstructing signal data (s(f), u(t)) by means of an appended system matrix (SM_AB) derived from at least two system matrices (SM_A, SM_B) for generating input image data (cin(r)),
b) selecting at least one voxel as selected voxel from the input image data (cin(r)) for generating output image data (cout(r)),
c) determining eigen-reconstruction signal data se n (f) by selecting at least one line entry of the appended system matrix (SM_AB) which corresponds to the at least one selected voxel,
d) reconstructing the eigen-reconstruction signal data se n (f) using the appended system matrix (SM_AB) for generating eigen-reconstruction image data ce(r),
e) subtracting the eigen-reconstruction image data ce(r) or weighted eigen-reconstruction image data ce′(r) from the input image data cin(r) for generating updated input image data cin n ′(r);
f) repeating steps b)-e) until a termination condition is met, wherein in step b) the selection is made from the updated input image data cin n ′(r) and wherein at least one selected voxel is added to the output image data cout(r); and
g) outputting, after the termination condition is met, the output image data cout(r) to a display device.
2 . The method according to claim 1 , wherein prior to step e) the eigen-reconstruction image data ce n (r) obtained in step d) is multiplied with a weighting factor to obtain weighted Eigen-reconstruction image data ce n ′(r) whose maximum intensity matches with the intensity of the selected voxel, and wherein in step e) the weighted eigen-reconstruction image data ce n ′(r) are used for subtraction.
3 . The method according to claim 1 , wherein prior to step d) the eigen-reconstruction signal data se n (f) obtained in step c) is multiplied with a weighting factor to obtain weighted eigen-reconstruction signal data se′ n (f)) whose maximum intensity matches with an intensity of the selected voxel, and wherein in step d) the weighted eigen-reconstruction signal data se′ n (f)) are used for eigen-reconstruction.
4 . The method according to claim 1 , wherein the at least two system matrices (SM_A, SM_B) are system matrices (SM_A, SM_B) of different particle classes (P 1 , P 2 ).
5 . The method according to claim 1 , wherein in step b) the selected voxel is a voxel of the input image data (cin(r)) having a highest signal intensity.
6 . The method according to claim 1 , wherein in step b) more than one voxel is selected.
7 . The method according to claim 6 , wherein all voxels having intensities exceeding a predefined selection threshold are selected.
8 . The method according to claim 1 , wherein a termination condition is determined and wherein the termination condition is met if intensities of all voxels of the updated input image data fall below a noise threshold.
9 . The method according to claim 1 , wherein the same reconstruction parameters are used for the reconstruction of the signal data in step a2) and for the eigen-reconstruction of the eigen-reconstruction signal data in step d).
10 . The method according to claim 1 wherein different reconstruction parameters are used for the reconstruction of the signal data in step a2) and for the eigen-reconstruction of the eigen-reconstruction signal data in step d).
11 . The method according to claim 1 , further comprising determining a distribution of tracers or of differently bound tracers within the sample being examined.
12 . The method according to claim 1 wherein the MPI signal data comprises signals collected from a medium containing particles that vary in size, shape and magnetic properties, and wherein the method further comprises determining whether the medium comprising the particles exceeds or falls below a threshold temperature and/or a threshold viscosity.
13 . The method according to claim 1 wherein at least one of the matrices is a background system matrix that does not contain particle signal information, and wherein the method further comprises performing a background correction of the MPI signal data.
14 . A system for visual representation of MPI image data (cout(r)) of a local concentration distribution of magnetic particles or a value derived from said concentration distribution, wherein the system is configured to perform the method according to claim 1 , comprising:
(i) said MPI apparatus for acquiring the MPI signal data s(f), u(t)),
(ii) a stored computer program that, when executed, generates the appended system matrix (SM_AB) from the at least two system matrices (SM_A, SM_B),
(iii) a stored computer program that, when executed, carries out the reconstruction of the eigen-reconstruction signal data se n (f) using the appended system matrix (SM_AB), and
(iv) said display device configured to display said output image data cout(r).