Další formáty:
BibTeX
LaTeX
RIS
@article{1641676,
author = {Kaushik, Sumit and Slovák, Jan},
article_location = {DORDRECHT},
article_number = {8},
doi = {http://dx.doi.org/10.1007/s10851-019-00897-w},
keywords = {Diffusion tensor imaging; Riemannian symmetric space; Quaternions; Similarity measures; Dimension reduction; Fourth-order tensor},
language = {eng},
issn = {0924-9907},
journal = {JOURNAL OF MATHEMATICAL IMAGING AND VISION},
title = {HARDI Segmentation via Fourth-Order Tensors and Anisotropy Preserving Similarity Measures},
url = {https://link.springer.com/article/10.1007/s10851-019-00897-w},
volume = {61},
year = {2019}
}
TY - JOUR
ID - 1641676
AU - Kaushik, Sumit - Slovák, Jan
PY - 2019
TI - HARDI Segmentation via Fourth-Order Tensors and Anisotropy Preserving Similarity Measures
JF - JOURNAL OF MATHEMATICAL IMAGING AND VISION
VL - 61
IS - 8
SP - 1221-1234
EP - 1221-1234
PB - SPRINGER
SN - 09249907
KW - Diffusion tensor imaging
KW - Riemannian symmetric space
KW - Quaternions
KW - Similarity measures
KW - Dimension reduction
KW - Fourth-order tensor
UR - https://link.springer.com/article/10.1007/s10851-019-00897-w
L2 - https://link.springer.com/article/10.1007/s10851-019-00897-w
N2 - In this work, we discuss the higher-order tensors appearing in high angular resolution diffusion tensor imaging, and we have tested two segmentation methods, the Riemannian spectral clustering and the deformable models, using several projections of the fourth-order tensors to the second-order ones, and diverse similarity measures on them. High angular resolution diffusion imaging has proved its effectiveness in modeling white matter brain structures along with the fiber intersection regions, which is of high importance in brain research. Along with other known projections, we observe that the diagonal components of the flattened fourth-order tensors also live in the well-known Riemannian symmetric space of symmetric positive-definite matrices. We discuss and compare several natural approximations of the distance on the latter space to be used in clustering and segmentation algorithms. The results show that some of the projections unfold the geometry of the higher-order tensors very well, and we also propose the exploitation of the spherical linear interpolation spectral quaternion metric, which proves to be very effective. The latter claims are supported by experimental comparison of the effectiveness of our algorithms with the more usual logarithmic Euclidean and spectral quaternionic metrics, in particular in the presence of noise. Our methods allow to distinguish individual objects in complex structures with high curvatures and crossings.
ER -
KAUSHIK, Sumit a Jan SLOVÁK. HARDI Segmentation via Fourth-Order Tensors and Anisotropy Preserving Similarity Measures. \textit{JOURNAL OF MATHEMATICAL IMAGING AND VISION}. DORDRECHT: SPRINGER, 2019, roč.~61, č.~8, s.~1221-1234. ISSN~0924-9907. Dostupné z: https://dx.doi.org/10.1007/s10851-019-00897-w.
|
