Abstract: In this note, a novel approach to the problem of estimation of orientation distribution functions (ODFs) in q-ball imaging is presented.

ABSTRACT. In this note, a novel approach to the problem of estimation of orientation distribution functions (ODFs) in q-ball imaging is presented.

Apr 14, 2010 · In this note, a novel approach to the problem of estimation of orientation distribution functions (ODFs) in q-ball imaging is presented.

The success of such a minimization is primarily due to the availability of spherical ridgelet transformation, which excels in sparsifying HARDI signals. What ...

Two different q- space regularization approaches (i.e., Laplace-Beltrami smoothness and spherical ridgelet sparsity) have been proposed to compensate for ...

Spatially regularized q-ball imaging using spherical ridgelets · O. MichailovichY. Rathi. Computer Science, Engineering. 2010 IEEE International Symposium on ...

51 results in 0.014 seconds. Simple view. Ellipse. Page size: 10, 50, 100, 1000 ... "spatially regularized q ball imaging using spherical ridgelets"^^<http ...

Mar 3, 2020 · Spatially regularized q-ball imaging using spherical ridgelets. In 2010 IEEE 7th International Symposium on Biomedical Imaging (ISBI) ...

Then, a HARDI signal S can be approximated by a linear combination AL of L spherical ridgelets, which can be found using the OMP algorithm [34] as follows.

Oct 22, 2024 · The success of such a minimization is primarily due to the availability of spherical ridgelet transformation, which excels in sparsifying HARDI ...