Academic Radiology
Volume 17, Issue 1 , Pages 67-74, January 2010

Automatic Identification of the Reference System Based on the Fourth Ventricular Landmarks in T1-weighted MR Images

  • Yili Fu, PhD

      Affiliations

    • State Key Laboratory of Robotics and System, Room 417, Building 2E, Science Park, Harbin Institute of Technology, No 2 Yikuang Street, Nangang District, Harbin, Heilongjiang, China
    • Bio-X Center, Room 417, Building 2E, Science Park, Harbin Institute of Technology, No 2 Yikuang Street, Nangang District, Harbin, Heilongjiang, China
    • ,
  • Wenpeng Gao, MD

      Affiliations

    • State Key Laboratory of Robotics and System, Room 417, Building 2E, Science Park, Harbin Institute of Technology, No 2 Yikuang Street, Nangang District, Harbin, Heilongjiang, China
    • Bio-X Center, Room 417, Building 2E, Science Park, Harbin Institute of Technology, No 2 Yikuang Street, Nangang District, Harbin, Heilongjiang, China
    • Corresponding Author InformationAddress correspondence to: W.G.
    • ,
  • Xiaoguang Chen, PhD

      Affiliations

    • Department of Neurosurgery, First Affiliated Hospital of Harbin Medical University, Harbin, China
    • ,
  • Minwei Zhu, PhD

      Affiliations

    • Department of Neurosurgery, First Affiliated Hospital of Harbin Medical University, Harbin, China
    • ,
  • Weigao Shen, MD

      Affiliations

    • Department of Anatomy, College of Basic Medicine of Beihua University, Jilin, China
    • ,
  • Shuguo Wang, PhD

      Affiliations

    • State Key Laboratory of Robotics and System, Room 417, Building 2E, Science Park, Harbin Institute of Technology, No 2 Yikuang Street, Nangang District, Harbin, Heilongjiang, China

Received 28 April 2009; accepted 13 July 2009. published online 07 September 2009.

Rationale and Objectives

The reference system based on the fourth ventricular landmarks (including the fastigial point and ventricular floor plane) is used in medical image analysis of the brain stem. The objective of this study was to develop a rapid, robust, and accurate method for the automatic identification of this reference system on T1-weighted magnetic resonance images.

Materials and Methods

The fully automated method developed in this study consisted of four stages: preprocessing of the data set, expectation-maximization algorithm–based extraction of the fourth ventricle in the region of interest, a coarse-to-fine strategy for identifying the fastigial point, and localization of the base point. The method was evaluated on 27 Brain Web data sets qualitatively and 18 Internet Brain Segmentation Repository data sets and 30 clinical scans quantitatively.

Results

The results of qualitative evaluation indicated that the method was robust to rotation, landmark variation, noise, and inhomogeneity. The results of quantitative evaluation indicated that the method was able to identify the reference system with an accuracy of 0.7 ± 0.2 mm for the fastigial point and 1.1 ± 0.3 mm for the base point. It took <6 seconds for the method to identify the related landmarks on a personal computer with an Intel Core 2 6300 processor and 2 GB of random-access memory.

Conclusion

The proposed method for the automatic identification of the reference system based on the fourth ventricular landmarks was shown to be rapid, robust, and accurate. The method has potentially utility in image registration and computer-aided surgery.

Key Words: Fastigial point, floor of the fourth ventricle, reference system, automatic localization

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 This work was supported by Self-Planned Task (SKLRS200802A01) of State Key Laboratory of Robotics and System (Harbin Institute of Technology, Harbin, China) and was partly supported by the Task (2007–241) of Heilongjiang Health Department, Task (11541204) of Heilongjiang Education Department, and National Science Foundation of China (60575016).

PII: S1076-6332(09)00411-5

doi:10.1016/j.acra.2009.07.013

Academic Radiology
Volume 17, Issue 1 , Pages 67-74, January 2010

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