3-D segmentation of articular cartilages by graph cuts using knee MR images from the osteoarthritis initiative

Hackjoon Shim, Soochan Lee, Bohyeong Kim, Cheng Tao, Samuel Chang, Il Dong Yun, Sang Uk Lee, Chian K Kwoh, Kyongtae Bae

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

3 Citations (Scopus)

Abstract

Knee osteoarthritis is the most common debilitating health condition affecting elderly population. MR imaging of the knee is highly sensitive for diagnosis and evaluation of the extent of knee osteoarthritis. Quantitative analysis of the progression of osteoarthritis is commonly based on segmentation and measurement of articular cartilage from knee MR images. Segmentation of the knee articular cartilage, however, is extremely laborious and technically demanding, because the cartilage is of complex geometry and thin and small in size. To improve precision and efficiency of the segmentation of the cartilage, we have applied a semi-automated segmentation method that is based on an s/t graph cut algorithm. The cost function was defined integrating regional and boundary cues. While regional cues can encode any intensity distributions of two regions, "object" (cartilage) and "background" (the rest), boundary cues are based on the intensity differences between neighboring pixels. For three-dimensional (3-D) segmentation, hard constraints are also specified in 3-D way facilitating user interaction. When our proposed semi-automated method was tested on clinical patients' MR images (160 slices, 0.7 mm slice thickness), a considerable amount of segmentation time was saved with improved efficiency, compared to a manual segmentation approach.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6914
DOIs
StatePublished - 2008
Externally publishedYes
EventMedical Imaging 2008: Image Processing - San Diego, CA, United States
Duration: Feb 17 2008Feb 19 2008

Other

OtherMedical Imaging 2008: Image Processing
CountryUnited States
CitySan Diego, CA
Period2/17/082/19/08

Fingerprint

Cartilage
Cost functions
Pixels
Health
Imaging techniques
Geometry
Chemical analysis

Keywords

  • Graph cuts
  • Knee cartilage
  • MR images
  • Segmentation

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Shim, H., Lee, S., Kim, B., Tao, C., Chang, S., Yun, I. D., ... Bae, K. (2008). 3-D segmentation of articular cartilages by graph cuts using knee MR images from the osteoarthritis initiative. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 6914). [691448] https://doi.org/10.1117/12.770887

3-D segmentation of articular cartilages by graph cuts using knee MR images from the osteoarthritis initiative. / Shim, Hackjoon; Lee, Soochan; Kim, Bohyeong; Tao, Cheng; Chang, Samuel; Yun, Il Dong; Lee, Sang Uk; Kwoh, Chian K; Bae, Kyongtae.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 6914 2008. 691448.

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

Shim, H, Lee, S, Kim, B, Tao, C, Chang, S, Yun, ID, Lee, SU, Kwoh, CK & Bae, K 2008, 3-D segmentation of articular cartilages by graph cuts using knee MR images from the osteoarthritis initiative. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 6914, 691448, Medical Imaging 2008: Image Processing, San Diego, CA, United States, 2/17/08. https://doi.org/10.1117/12.770887
Shim H, Lee S, Kim B, Tao C, Chang S, Yun ID et al. 3-D segmentation of articular cartilages by graph cuts using knee MR images from the osteoarthritis initiative. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 6914. 2008. 691448 https://doi.org/10.1117/12.770887
Shim, Hackjoon ; Lee, Soochan ; Kim, Bohyeong ; Tao, Cheng ; Chang, Samuel ; Yun, Il Dong ; Lee, Sang Uk ; Kwoh, Chian K ; Bae, Kyongtae. / 3-D segmentation of articular cartilages by graph cuts using knee MR images from the osteoarthritis initiative. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 6914 2008.
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