Shape-based acetabular cartilage segmentation: application to CT and MRI datasets

  • Pooneh R. TabriziEmail author
  • Reza A. Zoroofi
  • Futoshi Yokota
  • Takashi Nishii
  • Yoshinobu Sato
Original Article



A new method for acetabular cartilage segmentation in both computed tomography (CT) arthrography and magnetic resonance imaging (MRI) datasets with leg tension is developed and tested.


The new segmentation method is based on the combination of shape and intensity information. Shape information is acquired according to the predictable nonlinear relationship between the U-shaped acetabulum region and acetabular cartilage. Intensity information is obtained from the acetabular cartilage region automatically to complete the segmentation procedures. This method is evaluated using 54 CT arthrography datasets with two different radiation doses and 20 MRI datasets. Additionally, the performance of this method in identifying acetabular cartilage is compared with four other acetabular cartilage segmentation methods.


This method performed better than the comparison methods. Indeed, this method maintained good accuracy level for 74 datasets independent of the cartilage modality and with minimum user interaction in the bone segmentation procedures. In addition, this method was efficient in noisy conditions and in detection of the damaged cartilages with zero thickness, which confirmed its potential clinical usefulness.


Our new method proposes acetabular cartilage segmentation in three different datasets based on the combination of the shape and intensity information. This method executes well in situations where there are clear boundaries between the acetabular and femoral cartilages. However, the acetabular cartilage and pelvic bone information should be obtained from one dataset such as CT arthrography or MRI datasets with leg traction.


Acetabular cartilage CT arthrography Graph-Cut  K-OPLS MRI Pelvic bone 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights

For this type of study, formal consent is not required because this study is a retrospective study.

Informed consent

Written informed consent was not required for this study because this study is a retrospective study.

Supplementary material

11548_2015_1313_MOESM1_ESM.docx (1 mb)
Supplementary material 1 (docx 1041 KB)


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Copyright information

© CARS 2015

Authors and Affiliations

  • Pooneh R. Tabrizi
    • 1
    Email author
  • Reza A. Zoroofi
    • 1
  • Futoshi Yokota
    • 2
  • Takashi Nishii
    • 3
  • Yoshinobu Sato
    • 2
  1. 1.Control and Intelligent Processing Center of Excellence, School of Electrical and Computer EngineeringUniversity of TehranTehranIran
  2. 2.Imaging-Based Computational Biomedicine (ICB) Lab, Graduate School of Information ScienceNara Institute of Science and Technology (NAIST)OsakaJapan
  3. 3.Graduate School of MedicineOsaka UniversitySuita-shiJapan

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