[www] [BibTex]

Note: inproceedings, reconstruction, multi-patch

Abstract: The multi-patch approach in magnetic particle imaging is used to capture large field of views. System-matrix-based image reconstruction for this approach often considers a joint system of equations to minimize artifacts. Due to the prohibitive size of this inverse problem, reconstructions rely on iterative algorithms that do not need to keep the entire system matrix in memory. This work shows a graphical processing unit accelerated implementation of a generalized multi-patch operator. The achieved runtime improvements allow for multi-patch reconstructions using different optimization algorithms, which in turn allow for a flexible choice of regularization terms.

[www]

Note: inproceedings, reconstruction, multi-patch

Abstract: The multi-patch approach in magnetic particle imaging is used to capture large field of views. System-matrix-based image reconstruction for this approach often considers a joint system of equations to minimize artifacts. Due to the prohibitive size of this inverse problem, reconstructions rely on iterative algorithms that do not need to keep the entire system matrix in memory. This work shows a graphical processing unit accelerated implementation of a generalized multi-patch operator. The achieved runtime improvements allow for multi-patch reconstructions using different optimization algorithms, which in turn allow for a flexible choice of regularization terms.

[www] [BibTex]

Note: inproceedings, reconstruction, multi-patch

Abstract: The multi-patch approach in magnetic particle imaging is used to capture large field of views. System-matrix-based image reconstruction for this approach often considers a joint system of equations to minimize artifacts. Due to the prohibitive size of this inverse problem, reconstructions rely on iterative algorithms that do not need to keep the entire system matrix in memory. This work shows a graphical processing unit accelerated implementation of a generalized multi-patch operator. The achieved runtime improvements allow for multi-patch reconstructions using different optimization algorithms, which in turn allow for a flexible choice of regularization terms.

[www]

Note: inproceedings, reconstruction, multi-patch

Abstract: The multi-patch approach in magnetic particle imaging is used to capture large field of views. System-matrix-based image reconstruction for this approach often considers a joint system of equations to minimize artifacts. Due to the prohibitive size of this inverse problem, reconstructions rely on iterative algorithms that do not need to keep the entire system matrix in memory. This work shows a graphical processing unit accelerated implementation of a generalized multi-patch operator. The achieved runtime improvements allow for multi-patch reconstructions using different optimization algorithms, which in turn allow for a flexible choice of regularization terms.

[www]

Note: inproceedings, reconstruction, multi-patch

Abstract: The multi-patch approach in magnetic particle imaging is used to capture large field of views. System-matrix-based image reconstruction for this approach often considers a joint system of equations to minimize artifacts. Due to the prohibitive size of this inverse problem, reconstructions rely on iterative algorithms that do not need to keep the entire system matrix in memory. This work shows a graphical processing unit accelerated implementation of a generalized multi-patch operator. The achieved runtime improvements allow for multi-patch reconstructions using different optimization algorithms, which in turn allow for a flexible choice of regularization terms.

[www] [BibTex]

Note: inproceedings, reconstruction, multi-patch

Abstract: The multi-patch approach in magnetic particle imaging is used to capture large field of views. System-matrix-based image reconstruction for this approach often considers a joint system of equations to minimize artifacts. Due to the prohibitive size of this inverse problem, reconstructions rely on iterative algorithms that do not need to keep the entire system matrix in memory. This work shows a graphical processing unit accelerated implementation of a generalized multi-patch operator. The achieved runtime improvements allow for multi-patch reconstructions using different optimization algorithms, which in turn allow for a flexible choice of regularization terms.