Abstract
Anterior knee pain (AKP) is a common pathological condition. The problem causing knee pain is the abnormal patellar tracking mechanism. Kinematic approaches using MR images have been regarded of more accuracy in knee pain detection than stationary approaches. This paper proposes an automatic diagnosis based kinematic patellar tracking for AKP detection. The kinematic patellar tracking 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 experiment results demonstrate the prominent of the calculated inclination angles in detecting AKP.
| Original language | English |
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| Title of host publication | TENCON 2007 - 2007 IEEE Region 10 Conference |
| DOIs | |
| Publication status | Published - 2007 Dec 1 |
| Event | IEEE Region 10 Conference, TENCON 2007 - Taipei, Taiwan Duration: 2007 Oct 30 → 2007 Nov 2 |
Publication series
| Name | IEEE Region 10 Annual International Conference, Proceedings/TENCON |
|---|
Other
| Other | IEEE Region 10 Conference, TENCON 2007 |
|---|---|
| Country | Taiwan |
| City | Taipei |
| Period | 07-10-30 → 07-11-02 |
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
Cite this
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An automatic detection algorithm of MR images for knee pain problem. / Chung, Yi-Nung; Chou, Cheng Nan; Lan, Haw Chang; Ho, Wen Hsin.
TENCON 2007 - 2007 IEEE Region 10 Conference. 2007. 4428840 (IEEE Region 10 Annual International Conference, Proceedings/TENCON).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - An automatic detection algorithm of MR images for knee pain problem
AU - Chung, Yi-Nung
AU - Chou, Cheng Nan
AU - Lan, Haw Chang
AU - Ho, Wen Hsin
PY - 2007/12/1
Y1 - 2007/12/1
N2 - Anterior knee pain (AKP) is a common pathological condition. The problem causing knee pain is the abnormal patellar tracking mechanism. Kinematic approaches using MR images have been regarded of more accuracy in knee pain detection than stationary approaches. This paper proposes an automatic diagnosis based kinematic patellar tracking for AKP detection. The kinematic patellar tracking 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 experiment results demonstrate the prominent of the calculated inclination angles in detecting AKP.
AB - Anterior knee pain (AKP) is a common pathological condition. The problem causing knee pain is the abnormal patellar tracking mechanism. Kinematic approaches using MR images have been regarded of more accuracy in knee pain detection than stationary approaches. This paper proposes an automatic diagnosis based kinematic patellar tracking for AKP detection. The kinematic patellar tracking 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 experiment results demonstrate the prominent of the calculated inclination angles in detecting AKP.
UR - http://www.scopus.com/inward/record.url?scp=48649085546&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=48649085546&partnerID=8YFLogxK
U2 - 10.1109/TENCON.2007.4428840
DO - 10.1109/TENCON.2007.4428840
M3 - Conference contribution
AN - SCOPUS:48649085546
SN - 1424412722
SN - 9781424412723
T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON
BT - TENCON 2007 - 2007 IEEE Region 10 Conference
ER -