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Application of 3D‐MR image registration to monitor diseases around the knee joint
Author(s) -
Takao Masaki,
Sugano Nobuhiko,
Nishii Takashi,
Miki Hidenobu,
Koyama Tsuyoshi,
Masumoto Jun,
Sato Yoshinobu,
Tamura Shinichi,
Yoshikawa Hideki
Publication year - 2005
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.20435
Subject(s) - voxel , knee joint , imaging phantom , joint (building) , image registration , segmentation , consistency (knowledge bases) , tibia , nuclear medicine , femur , medicine , computer science , artificial intelligence , mathematics , anatomy , image (mathematics) , surgery , architectural engineering , engineering
Purpose To estimate the accuracy and consistency of a method using a voxel‐based MR image registration algorithm for precise monitoring of knee joint diseases. Materials and Methods Rigid body transformation was calculated using a normalized cross‐correlation (NCC) algorithm involving simple manual segmentation of the bone region based on its anatomical features. The accuracy of registration was evaluated using four phantoms, followed by a consistency test using MR data from the 11 patients with knee joint disease. Results The registration accuracy in the phantom experiment was 0.49 ± 0.19 mm (SD) for the femur and 0.56 ± 0.21 mm (SD) for the tibia. The consistency value in the experiment using clinical data was 0.69 ± 0.25 mm (SD) for the femur and 0.77 ± 0.37 mm (SD) for the tibia. These values were all smaller than a voxel (1.25 × 1.25 × 1.5 mm). Conclusion The present method based on an NCC algorithm can be used to register serial MR images of the knee joint with error on the order of a subvoxel. This method would be useful for precisely assessing therapeutic response and monitoring knee joint diseases; normalized cross‐correlation; accuracy J. Magn. Reson. Imaging 2005. © 2005 Wiley‐Liss, Inc.