Model-based segmentation of flexor tendons from magnetic resonance images of finger joints

H. C. Chen, C. K. Chen, Tai-Hua Yang, Li-Chieh Kuo, I. M. Jou, Fong-chin Su, Yung-Nien Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Trigger finger is a common hand disease, causing swelling, painful popping and clicking in moving the affected finger joint. To better evaluate patients with trigger finger, segmentation of flexor tendons from magnetic resonance (MR) images of finger joints, which can offer detailed structural information of tendons to clinicians, is essential. This paper presents a novel model-based method with three stages for automatically segmenting the flexor tendons. In the first stage, a set of tendon contour models (TCMs) is initialized from the most proximal cross-sectional image via two-step ellipse estimation. Each of the TCMs is then propagated to its distally adjacent image by affine registration. The propagation is sequentially performed along the proximal-distal direction until the most distal image is reached, as the second stage of segmentation. The TCMs on each cross-sectional image are refined in the last stage with the snake deformation. MR volumes of three subjects were used to validate the segmentation accuracy. Compared with the manual results, our method showed good accuracy with small average margins of errors (within 0.5 mm) and large overlapping ratio (dice similarity coefficient above 0.8). Overall, the proposed method has great potential for morphological change assessment of flexor tendons and pulley-tendon system modeling for image guided surgery.

Original languageEnglish
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages8009-8012
Number of pages4
DOIs
Publication statusPublished - 2011 Dec 26
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: 2011 Aug 302011 Sep 3

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period11-08-3011-09-03

Fingerprint

Finger Joint
Tendons
Magnetic resonance
Magnetic Resonance Spectroscopy
Fingers
Computer-Assisted Surgery
Pulleys
Snakes
Surgery
Swelling
Hand

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Chen, H. C., Chen, C. K., Yang, T-H., Kuo, L-C., Jou, I. M., Su, F., & Sun, Y-N. (2011). Model-based segmentation of flexor tendons from magnetic resonance images of finger joints. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 (pp. 8009-8012). [6091975] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/IEMBS.2011.6091975
Chen, H. C. ; Chen, C. K. ; Yang, Tai-Hua ; Kuo, Li-Chieh ; Jou, I. M. ; Su, Fong-chin ; Sun, Yung-Nien. / Model-based segmentation of flexor tendons from magnetic resonance images of finger joints. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. 2011. pp. 8009-8012 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).
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abstract = "Trigger finger is a common hand disease, causing swelling, painful popping and clicking in moving the affected finger joint. To better evaluate patients with trigger finger, segmentation of flexor tendons from magnetic resonance (MR) images of finger joints, which can offer detailed structural information of tendons to clinicians, is essential. This paper presents a novel model-based method with three stages for automatically segmenting the flexor tendons. In the first stage, a set of tendon contour models (TCMs) is initialized from the most proximal cross-sectional image via two-step ellipse estimation. Each of the TCMs is then propagated to its distally adjacent image by affine registration. The propagation is sequentially performed along the proximal-distal direction until the most distal image is reached, as the second stage of segmentation. The TCMs on each cross-sectional image are refined in the last stage with the snake deformation. MR volumes of three subjects were used to validate the segmentation accuracy. Compared with the manual results, our method showed good accuracy with small average margins of errors (within 0.5 mm) and large overlapping ratio (dice similarity coefficient above 0.8). Overall, the proposed method has great potential for morphological change assessment of flexor tendons and pulley-tendon system modeling for image guided surgery.",
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Chen, HC, Chen, CK, Yang, T-H, Kuo, L-C, Jou, IM, Su, F & Sun, Y-N 2011, Model-based segmentation of flexor tendons from magnetic resonance images of finger joints. in 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011., 6091975, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 8009-8012, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011, Boston, MA, United States, 11-08-30. https://doi.org/10.1109/IEMBS.2011.6091975

Model-based segmentation of flexor tendons from magnetic resonance images of finger joints. / Chen, H. C.; Chen, C. K.; Yang, Tai-Hua; Kuo, Li-Chieh; Jou, I. M.; Su, Fong-chin; Sun, Yung-Nien.

33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. 2011. p. 8009-8012 6091975 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Chen HC, Chen CK, Yang T-H, Kuo L-C, Jou IM, Su F et al. Model-based segmentation of flexor tendons from magnetic resonance images of finger joints. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. 2011. p. 8009-8012. 6091975. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/IEMBS.2011.6091975