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Erschienen in: International Journal of Computer Assisted Radiology and Surgery 4/2015

01.04.2015 | Review Article

Acetabular cartilage segmentation in CT arthrography based on a bone-normalized probabilistic atlas

verfasst von: Pooneh R. Tabrizi, Reza A. Zoroofi, Futoshi Yokota, Satoru Tamura, Takashi Nishii, Yoshinobu Sato

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 4/2015

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Abstract

Purpose

   Determination of acetabular cartilage loss in the hip joint is a clinically significant metric that requires image segmentation. A new semiautomatic method to segment acetabular cartilage in computed tomography (CT) arthrography scans was developed and tested.

Methods

   A semiautomatic segmentation method was developed based on the combination of anatomical and statistical information. Anatomical information is identified using the pelvic bone position and the contact area between cartilage and bone. Statistical information is acquired from CT intensity modeling of acetabular cartilage and adjacent tissue structures. This method was applied to the identification of acetabular cartilages in 37 intra-articular CT arthrography scans.

Results

The semiautomatic anatomical–statistical method performed better than other segmentation methods. The semiautomatic method was effective in noisy scans and was able to detect damaged cartilage.

Conclusions

   The new semiautomatic method segments acetabular cartilage by fully utilizing the statistical and anatomical information in CT arthrography datasets. This method for hip joint cartilage segmentation has potential for use in many clinical applications.
Literatur
1.
Zurück zum Zitat Cicuttini F, Forbes A, Morris K, Woodford N, Stuckey S (2000) Determining the volume of hip cartilage by magnetic resonance imaging. Radiography 6(2):79–82CrossRef Cicuttini F, Forbes A, Morris K, Woodford N, Stuckey S (2000) Determining the volume of hip cartilage by magnetic resonance imaging. Radiography 6(2):79–82CrossRef
3.
Zurück zum Zitat Nishii T, Sugano N, Sato Y, Tanaka H, Miki H, Yoshikawa H (2004) Three-dimensional distribution of acetabular cartilage thickness in patients with hip dysplasia: a fully automated computational analysis of mr imaging. Osteoarthr Cartil 12(8):650–657CrossRefPubMed Nishii T, Sugano N, Sato Y, Tanaka H, Miki H, Yoshikawa H (2004) Three-dimensional distribution of acetabular cartilage thickness in patients with hip dysplasia: a fully automated computational analysis of mr imaging. Osteoarthr Cartil 12(8):650–657CrossRefPubMed
4.
Zurück zum Zitat Tamura S, Nishii T, Shiomi T, Yamazaki Y, Murase K, Yoshikawa H, Sugano N (2012) Three-Dimensional patterns of early acetabular cartilage damage in hip dysplasia; a high-resolutional ct arthrography study. Osteoarthr Carti 20(7):646–652CrossRef Tamura S, Nishii T, Shiomi T, Yamazaki Y, Murase K, Yoshikawa H, Sugano N (2012) Three-Dimensional patterns of early acetabular cartilage damage in hip dysplasia; a high-resolutional ct arthrography study. Osteoarthr Carti 20(7):646–652CrossRef
5.
Zurück zum Zitat Mechlenburg I, Nyengaard JR, Gelineck J, Soballe K (2007) Cartilage thickness in the hip joint measured by mri and stereology—a methodological study. Osteoarthr Cartil 15(4):366–371CrossRefPubMed Mechlenburg I, Nyengaard JR, Gelineck J, Soballe K (2007) Cartilage thickness in the hip joint measured by mri and stereology—a methodological study. Osteoarthr Cartil 15(4):366–371CrossRefPubMed
6.
Zurück zum Zitat Cheng Y, Wang S, Yamazaki T, Zhao J, Nakajima Y, Tamura S (2007) Hip cartilage thickness measurement accuracy improvement. Comput Med Imag Graph 31(8):643–655CrossRef Cheng Y, Wang S, Yamazaki T, Zhao J, Nakajima Y, Tamura S (2007) Hip cartilage thickness measurement accuracy improvement. Comput Med Imag Graph 31(8):643–655CrossRef
7.
Zurück zum Zitat Khanmohammadi M, Zoroofi RA, Nishii T, Tanaka H, Sato Y (2009) A hybrid technique for thickness-map visualization of the hip cartilages in mri. IEICE Trans Inf Syst E92-D(11):2253–2263 Khanmohammadi M, Zoroofi RA, Nishii T, Tanaka H, Sato Y (2009) A hybrid technique for thickness-map visualization of the hip cartilages in mri. IEICE Trans Inf Syst E92-D(11):2253–2263
8.
Zurück zum Zitat Baniasadipour A, Zoroofi RA, Sato Y, Nishii T, Tanaka H (2011) Automated knowledge-based segmentation and analysis of the hip bones and cartilages using multi-slice ct data. Imag Sci 59(5):253–266CrossRef Baniasadipour A, Zoroofi RA, Sato Y, Nishii T, Tanaka H (2011) Automated knowledge-based segmentation and analysis of the hip bones and cartilages using multi-slice ct data. Imag Sci 59(5):253–266CrossRef
9.
Zurück zum Zitat Raynauld JP, Kauffmann C, Beaudoin G, Berthiaume MJ, de Guisei JA, Bloch DA, Camacho F, Godbout B et al (2003) Reliability of a quantification imaging system using magnetic resonance images to measure cartilage thickness and volume in human normal and osteoarthritic knees. Osteoarthr Cartil 11(5):351–360CrossRefPubMed Raynauld JP, Kauffmann C, Beaudoin G, Berthiaume MJ, de Guisei JA, Bloch DA, Camacho F, Godbout B et al (2003) Reliability of a quantification imaging system using magnetic resonance images to measure cartilage thickness and volume in human normal and osteoarthritic knees. Osteoarthr Cartil 11(5):351–360CrossRefPubMed
10.
Zurück zum Zitat Williams TG, Holmes AP, Waterton JC, Maciewicz RA, Hutchinson CE, Moots RJ, Nash AFP, Taylor CJ (2010) Anatomically corresponded regional analysis of cartilage in asymptomatic and osteoarthritic knees by statistical shape modelling of the bone. IEEE Trans Med Imaging 29(8):1541–1559CrossRefPubMed Williams TG, Holmes AP, Waterton JC, Maciewicz RA, Hutchinson CE, Moots RJ, Nash AFP, Taylor CJ (2010) Anatomically corresponded regional analysis of cartilage in asymptomatic and osteoarthritic knees by statistical shape modelling of the bone. IEEE Trans Med Imaging 29(8):1541–1559CrossRefPubMed
11.
Zurück zum Zitat Glocker B, Komodakis N, Paragios N, Glaser C, Tziritas G, Navab N (2007) Primal/dual linear programming and statistical atlases for cartilage segmentation. Proc MICCAI 10:536–543 Glocker B, Komodakis N, Paragios N, Glaser C, Tziritas G, Navab N (2007) Primal/dual linear programming and statistical atlases for cartilage segmentation. Proc MICCAI 10:536–543
12.
Zurück zum Zitat Solloway S, Hutchinson CE, Waterton JC, Taylor CJ (1997) The use of active shape models for making thickness measurements of articular cartilage from mr images. Magn Reson Med 37(6):943–952CrossRefPubMed Solloway S, Hutchinson CE, Waterton JC, Taylor CJ (1997) The use of active shape models for making thickness measurements of articular cartilage from mr images. Magn Reson Med 37(6):943–952CrossRefPubMed
13.
Zurück zum Zitat Lee S, Park SH, Shim H, Yun ID, Lee SU (2011) Optimization of local shape and appearance probabilities for segmentation of knee cartilage in 3-D MR images. Comput Vis Image Und 115(12):1710–1720CrossRef Lee S, Park SH, Shim H, Yun ID, Lee SU (2011) Optimization of local shape and appearance probabilities for segmentation of knee cartilage in 3-D MR images. Comput Vis Image Und 115(12):1710–1720CrossRef
14.
Zurück zum Zitat Fripp J, Crozier S, Warfield SK, Ourselin S (2010) Automatic segmentation and quantitative analysis of the articular cartilages from magnetic resonance images of the knee. IEEE Trans Med Imag 29(1):55–64CrossRef Fripp J, Crozier S, Warfield SK, Ourselin S (2010) Automatic segmentation and quantitative analysis of the articular cartilages from magnetic resonance images of the knee. IEEE Trans Med Imag 29(1):55–64CrossRef
15.
Zurück zum Zitat Zhang K, Lu W, Marziliano P (2013) Automatic knee cartilage segmentation from multi-contrast mr images using support vector machine classification with spatial dependencies. Magn Reson Im 31(10):1731–1743 Zhang K, Lu W, Marziliano P (2013) Automatic knee cartilage segmentation from multi-contrast mr images using support vector machine classification with spatial dependencies. Magn Reson Im 31(10):1731–1743
16.
Zurück zum Zitat Yin Y, Zhang X, Williams R, Wu X, Anderson DD, Sonka M (2010) LOGISMOS-layered optimal graph image segmentation of multiple objects and surfaces: cartilage segmentation in the knee joint. IEEE Trans Med Imaging 29(12):2023–2037CrossRefPubMedCentralPubMed Yin Y, Zhang X, Williams R, Wu X, Anderson DD, Sonka M (2010) LOGISMOS-layered optimal graph image segmentation of multiple objects and surfaces: cartilage segmentation in the knee joint. IEEE Trans Med Imaging 29(12):2023–2037CrossRefPubMedCentralPubMed
17.
Zurück zum Zitat Kauffmann C, Gravel P, Godbout B, Gravel A, Beaudoin G, Raynauld JP, Martel-Pelletier J, Pelletier JP, de Guise JA (2003) Computer-aided method for quantification of cartilage thickness and volume changes using mri: validation study using a synthetic model. IEEE Trans Biomed Eng 50(8):978–988CrossRefPubMed Kauffmann C, Gravel P, Godbout B, Gravel A, Beaudoin G, Raynauld JP, Martel-Pelletier J, Pelletier JP, de Guise JA (2003) Computer-aided method for quantification of cartilage thickness and volume changes using mri: validation study using a synthetic model. IEEE Trans Biomed Eng 50(8):978–988CrossRefPubMed
18.
Zurück zum Zitat Tang J, Millington S, Acton ST, Crandall J, Hurwitz S (2006) Surface extraction and thickness measurement of the articular cartilage from mr images using directional gradient vector flow snakes. IEEE Trans Biomed Eng 53(5):896–907CrossRefPubMed Tang J, Millington S, Acton ST, Crandall J, Hurwitz S (2006) Surface extraction and thickness measurement of the articular cartilage from mr images using directional gradient vector flow snakes. IEEE Trans Biomed Eng 53(5):896–907CrossRefPubMed
19.
Zurück zum Zitat Okada T, Linguraru MG, Hori M, Summers RM, Tomiyama N, Sato Y (2013) Abdominal multi-organ ct segmentation using organ correlation graph and prediction-based shape and location priors. Proc MICCAI 8151:275–282 Okada T, Linguraru MG, Hori M, Summers RM, Tomiyama N, Sato Y (2013) Abdominal multi-organ ct segmentation using organ correlation graph and prediction-based shape and location priors. Proc MICCAI 8151:275–282
20.
Zurück zum Zitat Boykov YY, Jolly MP (2001) Interactive graph cuts for optimal boundary & region segmentation of objects in n-d images. Proc ICCV I:12–105 Boykov YY, Jolly MP (2001) Interactive graph cuts for optimal boundary & region segmentation of objects in n-d images. Proc ICCV I:12–105
21.
Zurück zum Zitat Rueckert D, Sonoda LI, Hayes C, Hill DLG, Leach MO, Hawkes DJ (1999) Nonrigid registration using free-form deformations: application to breast mr images. Trans Med Imaging 18(8):712–721 Rueckert D, Sonoda LI, Hayes C, Hill DLG, Leach MO, Hawkes DJ (1999) Nonrigid registration using free-form deformations: application to breast mr images. Trans Med Imaging 18(8):712–721
22.
Zurück zum Zitat Yokota F, Okada T, Takao M, Sugano N, Tada Y, Sato Y (2009) Automated segmentation of the femur and pelvis from 3d ct data of diseased hip using hierarchical statistical shape model of joint structure. Proc MICCAI 12:811–818 Yokota F, Okada T, Takao M, Sugano N, Tada Y, Sato Y (2009) Automated segmentation of the femur and pelvis from 3d ct data of diseased hip using hierarchical statistical shape model of joint structure. Proc MICCAI 12:811–818
23.
Zurück zum Zitat Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Sys Man Cyber 9(1):62–66CrossRef Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Sys Man Cyber 9(1):62–66CrossRef
24.
Zurück zum Zitat Carr JC, Beatson RK, Cherrie JB, Mitchell TJ, Fright WR, McCallum BC, Evans TR (2001) Reconstruction and representation of 3d objects with radial basis functions. In: Proceedings of ACM SIGGRAPH, pp 67–76 Carr JC, Beatson RK, Cherrie JB, Mitchell TJ, Fright WR, McCallum BC, Evans TR (2001) Reconstruction and representation of 3d objects with radial basis functions. In: Proceedings of ACM SIGGRAPH, pp 67–76
25.
Zurück zum Zitat Dice LR (1945) Measures of the amount of ecologic association between species. Ecology 26(3):299–302CrossRef Dice LR (1945) Measures of the amount of ecologic association between species. Ecology 26(3):299–302CrossRef
26.
Zurück zum Zitat Heimann T, van Ginneken B, Styner MA, Arzhaeva Y, Aurich V, Bauer C, Beck A, Becker C et al (2009) Comparison and evaluation of methods for liver segmentation from ct datasets. IEEE Trans Med Imaging 28(8):1251–1265CrossRefPubMed Heimann T, van Ginneken B, Styner MA, Arzhaeva Y, Aurich V, Bauer C, Beck A, Becker C et al (2009) Comparison and evaluation of methods for liver segmentation from ct datasets. IEEE Trans Med Imaging 28(8):1251–1265CrossRefPubMed
Metadaten
Titel
Acetabular cartilage segmentation in CT arthrography based on a bone-normalized probabilistic atlas
verfasst von
Pooneh R. Tabrizi
Reza A. Zoroofi
Futoshi Yokota
Satoru Tamura
Takashi Nishii
Yoshinobu Sato
Publikationsdatum
01.04.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Computer Assisted Radiology and Surgery / Ausgabe 4/2015
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI
https://doi.org/10.1007/s11548-014-1101-1

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