Limits to the Accuracy of 3D Thickness Measurement in Magnetic Resonance Images

  • Yoshinobu Sato
  • Katsuyuki Nakanishi
  • Hisashi Tanaka
  • Takashi Nishii
  • Nobuhiko Sugano
  • Hironobu Nakamura
  • Takahiro Ochi
  • Shinichi Tamura
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2208)

Abstract

Measuring the thickness of sheet-like (or plate-like) anatomical structures, such as articular cartilages and brain cortex, in 3D magnetic resonance (MR) images is often an important diagnostic procedure. The purpose of this paper is to investigate the fundamental limits to the accuracy of thickness determination in MR images. Given imaging and postprocessing parameters, the characteristics of thickness determination accuracy are derived by means of a theoretical simulation method, focusing especially on the e.ect of sheet structure orientation on accuracy in the case of noncubic (anisotropic) voxels. The theoretical simulation was validated by in vitro experiments.

Keywords

Articular Cartilage Cartilage Thickness Sheet Structure Thickness Determination Resected Femoral Head 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Download to read the full conference paper text

References

  1. 1.
    Jonsson K, Buckwalter K, Helvie M, Niklason L, and Martel W: Precision of hyaline cartilage thickness measurements, Acta Radiol, 33, 234–239 (1992).Google Scholar
  2. 2.
    Hodler J, Trundell D, Pathria MN, and Resnick D: Width of the articular cartilage of the hip: quantification by using fat-suppression spin-echo MR imaging in cadavers, AJR Am J Roentgenol, 159, 351–355 (1992).Google Scholar
  3. 3.
    Eckstein F, Gavazzini A, Sittek H, Haubner M, Losch A, Milz S, Englmeier K-H, Schulte E, Putz R, and Reiser M: Determination of knee joint cartilage thickness using three-dimensional magnetic resonance chondro-crassometry (3D MR-CCM), Magn Reson Med, 36, 256–265 (1996).CrossRefGoogle Scholar
  4. 4.
    Solloway S, Hutchinson CE, Waterton JG, Taylor CJ, The use of active shape models for making thickness measurements of articular cartilage from MR images, Magn Reson Med, 37, 943–952 (1997).CrossRefGoogle Scholar
  5. 5.
    McGibbon CA, Dupuy DE, Palmer WE, and Krebs D.: Cartilage and subchondral bone thickness distribution with MR imaging, Acad Radiol, 5, 20–25 (1998).CrossRefGoogle Scholar
  6. 6.
    McGibbon CA, Palmer WE, and Krebs DE: A general computing method for spatial cartilage thickness from co-planar MRI, Med Eng Phys, 20, 169–176 (1998).CrossRefGoogle Scholar
  7. 7.
    Nakanishi N, Tanaka H, Nishii T, Masuhara K, Narumi Y, and Nakamura H: MR evaluation of the articular cartilage of the femoral head during traction, Acta Radiol, 40, 60–63 (1999).CrossRefGoogle Scholar
  8. 8.
    Sato Y, Kubota T, Nakanishi K, Sugano N, Nishii T, Ohzono K, Nakamura H, Ochi O, and Tamura S: Three-dimensional reconstruction and quantification of hip joint cartilages from magnetic resonance images, Lecture Notes in Computer Science (LNCS), 1679 (MICCAI’99), 338–347 (1999).Google Scholar
  9. 9.
    Zeng X, Staib LH, Schults RT, and Duncan JS: Segmentation and measurement of the cortex from 3-D MR images using coupled-surfaces propagation, IEEE Trans Med Imaging, 18, 927–937 (1999).CrossRefGoogle Scholar
  10. 10.
    Magnotta VA, Andreasen NC, Schultz SK, Harris G, Cizadlo T, Heckel D, Nopoulos P, Flaum M: Quantitative in vivo measurement of gyrification in the human brain: changes associated with aging, Cereb Cortex, 9, 151–160, 1999.CrossRefGoogle Scholar
  11. 11.
    Parker DL, Du YP, and Davis WL: The voxel sensitivity function in Fourier transform imaging: applications to magnetic resonance angiography, Magn Reson Med, 33, 156–162 (1995).CrossRefGoogle Scholar
  12. 12.
    Hoogeveen, RM, Bakker CJG, and Viergever MA: Limits to the accuracy of vessel diameter measurement in MR angiography, J Magn Reson Imaging, 8, 1228–1235 (1998).CrossRefGoogle Scholar
  13. 13.
    Hylton NM, Simovsky I, Li AJ, Hale JD: Impact of section doubling on MR angiography, Radiology, 185, 899–902 (1992).Google Scholar
  14. 14.
    Du YP, Parker DL, Davis WL, Cao G: Reduction of partial-volume artifacts with zero-filled interpolation in three-dimensional MR angiography, J Magn Reson Imaging, 4, 733–741 (1995).CrossRefGoogle Scholar
  15. 15.
    Sato Y, Nakajima S, Shiraga N, Atsumi H, Yoshida S, Koller T, Guido G, and Kikinis R: Three dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images, Med Image Anal, 2, 143–168 (1998).CrossRefGoogle Scholar
  16. 16.
    Sato Y, Westin C-F, Bhalerao A, Nakajima S, Shiraga N, Tamura S, and Kikinis R: Tissue classification based on 3D local intensity structures for volume rendering, IEEE Transactions on Visualization and Computer Graphics, 6, 160–180 (2000).CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Yoshinobu Sato
    • 1
  • Katsuyuki Nakanishi
    • 2
  • Hisashi Tanaka
    • 2
  • Takashi Nishii
    • 3
  • Nobuhiko Sugano
    • 3
  • Hironobu Nakamura
    • 2
  • Takahiro Ochi
    • 4
  • Shinichi Tamura
    • 1
  1. 1.Division of Interdisciplinary Image AnalysisOsaka University Graduate School of MedicineJapan
  2. 2.Department of RadiologyOsaka University Graduate School of MedicineJapan
  3. 3.Department of Orthopaedic SurgeryOsaka University Graduate School of MedicineJapan
  4. 4.Division of Computer Integrated Orthopaedic SurgeryOsaka University Graduate School of MedicineJapan

Personalised recommendations