TY - GEN
T1 - Automatic registration of the selected human body parts on the basis of entropy and energy measure of fuzziness
AU - Zarychta, Piotr
AU - Zarychta-Bargiela, Anna
PY - 2009
Y1 - 2009
N2 - This paper shows an automatic registration method of the A- and B-group of MRI brain and knee based on the entropy and energy measure of fuzziness. In the first case the time difference between recording the A-group and the B-group is equal six months. In the second case the registration process relies on comparison of each T1-weighted MRI slice with each T2-weighted MRI slice. This procedure has been tested on an overview of clinical exams with misalignment of T1- and T2-weighted MRI knee series, where patient motion has caused a mutual shift of slices. In the both events, first, two sequences (A- and B-group and T1- and T2-weighted series) are converted to a fuzzy representation. Then, the entropy and energy measures are employed in the NCC and GD methods. The alignment based on energy and entropy fuzzy measures shows a significant improvement in comparison with the implementation of the original image. This method has been implemented in MatLab and tested on the clinical exams of MRI images.
AB - This paper shows an automatic registration method of the A- and B-group of MRI brain and knee based on the entropy and energy measure of fuzziness. In the first case the time difference between recording the A-group and the B-group is equal six months. In the second case the registration process relies on comparison of each T1-weighted MRI slice with each T2-weighted MRI slice. This procedure has been tested on an overview of clinical exams with misalignment of T1- and T2-weighted MRI knee series, where patient motion has caused a mutual shift of slices. In the both events, first, two sequences (A- and B-group and T1- and T2-weighted series) are converted to a fuzzy representation. Then, the entropy and energy measures are employed in the NCC and GD methods. The alignment based on energy and entropy fuzzy measures shows a significant improvement in comparison with the implementation of the original image. This method has been implemented in MatLab and tested on the clinical exams of MRI images.
KW - Energy measure of fuzziness
KW - Entropy measure of fuzziness
KW - Registration
KW - Similarity measures
UR - https://www.scopus.com/pages/publications/80051498551
U2 - 10.3182/20090210-3-cz-4002.00052
DO - 10.3182/20090210-3-cz-4002.00052
M3 - Conference contribution
AN - SCOPUS:80051498551
SN - 9783902661418
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
SP - 260
EP - 265
BT - 9th IFAC Workshop on Programmable Devices and Embedded Systems, PDES 2009 - Proceedings
PB - IFAC Secretariat
ER -