Abstract
Kinematic approaches using MR images have been regarded of more accuracy in knee pain (AKP) detection than stationary approaches. However, the challenge in segmenting femur, patellar and tibia due to the intensity non-uniformity caused by magnetic propagation degradation in MR images, and the strong adhesion of the soft tissue around the knee organs, has restricted the use of kinematic approaches. This paper proposes a combinatorial based kinematic patellar tracking (CKPT) for AKP detection. The CKPT uses a hybrid approach for extracting knee organs, where an edge-constrained wavelet enhancement followed by moment preserving segmentation is employed for conquering the soft tissue adhesion for extracting the femur and tibia from axial MR images, and a sliding window based moment preserving for resolving the segmentation difficulty associated with intensity non-uniformity in saggital MR images. The location constraints are then applied for extracting landmark points from femur and patellar, and three inclination angles reflecting patellar position and orientation, during leg movement, are calculated as the measurement of patellar dislocation. The experiment shows that the hybrid approach can accurately extract femur, patellar and tibia. It also demonstrates the prominent of the calculated inclination angles in detecting AKP.
| Original language | English |
|---|---|
| Pages (from-to) | 1653-1659 |
| Number of pages | 7 |
| Journal | Computers in Biology and Medicine |
| Volume | 37 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 2007 Nov 1 |
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Health Informatics
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Kinematic patellar tracking from MR images for knee pain analysis. / Chung, Yi-Nung; Chou, Cheng Nan; Lan, Haw Chang; Ho, Wen Hsin.
In: Computers in Biology and Medicine, Vol. 37, No. 11, 01.11.2007, p. 1653-1659.Research output: Contribution to journal › Article
TY - JOUR
T1 - Kinematic patellar tracking from MR images for knee pain analysis
AU - Chung, Yi-Nung
AU - Chou, Cheng Nan
AU - Lan, Haw Chang
AU - Ho, Wen Hsin
PY - 2007/11/1
Y1 - 2007/11/1
N2 - Kinematic approaches using MR images have been regarded of more accuracy in knee pain (AKP) detection than stationary approaches. However, the challenge in segmenting femur, patellar and tibia due to the intensity non-uniformity caused by magnetic propagation degradation in MR images, and the strong adhesion of the soft tissue around the knee organs, has restricted the use of kinematic approaches. This paper proposes a combinatorial based kinematic patellar tracking (CKPT) for AKP detection. The CKPT uses a hybrid approach for extracting knee organs, where an edge-constrained wavelet enhancement followed by moment preserving segmentation is employed for conquering the soft tissue adhesion for extracting the femur and tibia from axial MR images, and a sliding window based moment preserving for resolving the segmentation difficulty associated with intensity non-uniformity in saggital MR images. The location constraints are then applied for extracting landmark points from femur and patellar, and three inclination angles reflecting patellar position and orientation, during leg movement, are calculated as the measurement of patellar dislocation. The experiment shows that the hybrid approach can accurately extract femur, patellar and tibia. It also demonstrates the prominent of the calculated inclination angles in detecting AKP.
AB - Kinematic approaches using MR images have been regarded of more accuracy in knee pain (AKP) detection than stationary approaches. However, the challenge in segmenting femur, patellar and tibia due to the intensity non-uniformity caused by magnetic propagation degradation in MR images, and the strong adhesion of the soft tissue around the knee organs, has restricted the use of kinematic approaches. This paper proposes a combinatorial based kinematic patellar tracking (CKPT) for AKP detection. The CKPT uses a hybrid approach for extracting knee organs, where an edge-constrained wavelet enhancement followed by moment preserving segmentation is employed for conquering the soft tissue adhesion for extracting the femur and tibia from axial MR images, and a sliding window based moment preserving for resolving the segmentation difficulty associated with intensity non-uniformity in saggital MR images. The location constraints are then applied for extracting landmark points from femur and patellar, and three inclination angles reflecting patellar position and orientation, during leg movement, are calculated as the measurement of patellar dislocation. The experiment shows that the hybrid approach can accurately extract femur, patellar and tibia. It also demonstrates the prominent of the calculated inclination angles in detecting AKP.
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UR - http://www.scopus.com/inward/citedby.url?scp=34548420278&partnerID=8YFLogxK
U2 - 10.1016/j.compbiomed.2007.04.002
DO - 10.1016/j.compbiomed.2007.04.002
M3 - Article
C2 - 17669391
AN - SCOPUS:34548420278
VL - 37
SP - 1653
EP - 1659
JO - Computers in Biology and Medicine
JF - Computers in Biology and Medicine
SN - 0010-4825
IS - 11
ER -