Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012 Feb;25(1):110-20.
doi: 10.1007/s10278-011-9384-z.

Locating the reference point of symphysis pubis in axial CT images

Jiyong Oh  1 , Dae Chul Jung, Chong-Ho Choi
Affiliations

Locating the reference point of symphysis pubis in axial CT images

Jiyong Oh et al. J Digit Imaging. 2012 Feb.

Abstract

In this paper, we present an effective method to determine the reference point of symphysis pubis (SP) in an axial stack of CT images to facilitate image registration for pelvic cancer treatment. In order to reduce the computational time, the proposed method consists of two detection parts, the coarse detector, and the fine detector. The detectors check each image patch whether it contains the characteristic structure of SP. The coarse detector roughly determines the location of the reference point of SP using three types of information, which are the location and intensity of an image patch, the SP appearance, and the geometrical structure of SP. The fine detector examines around the location found by the coarse detection to refine the location of the reference point of SP. In the experiment, the average location error of the propose method was 2.23 mm, which was about the side length of two pixels. Considering that the average location error by a radiologist is 0.77 mm, the proposed method finds the reference point quite accurately. Since it takes about 10 s to locate the reference point from a stack of CT images, it is fast enough to use in real time to facilitate image registration of CT images for pelvic cancer treatment.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Successive CT images with the structure of SP and their levels in an axial stack
Fig. 2
Fig. 2
Overall structure of the proposed method
Fig. 3
Fig. 3
Detection window and image patches in an image of 128 × 128 pixels
Fig. 4
Fig. 4
The hybrid cascade detector in the coarse detection
Fig. 5
Fig. 5
Four types of Haar-like features
Fig. 6
Fig. 6
Some of the SP patches
Fig. 7
Fig. 7
Negative samples
Fig. 8
Fig. 8
Distributions of dW
Fig. 9
Fig. 9
Clustering of the base points. Each point denotes a base point
Fig. 10
Fig. 10
The R-points detected from a pair of CT image stacks of the same patient
Fig. 11
Fig. 11
Errors of the 49 stacks in the test set. These figures show the level errors, the location errors in the xy plane, and the cumulative distribution of the location errors in three-dimensional space, respectively
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Hayat M. Cancer Imaging Volume 2: Instrumentation and applications. New York: Academic; 2007.
    1. Hajnal JV, Hawkes DJ, Hill DL. Medical image registration. New York: CRC; 2001.
    1. Zitova B, Flusser J. Image registration methods: a survey. Image Vis Comput. 2003;21(11):977–1000. doi: 10.1016/S0262-8856(03)00137-9. - DOI
    1. Coselmon MM, Balter JM, McShan DL, Kessler ML. Mutual information based CT registration of the lung at exhale and inhale breathing states using thin-plate splines. Med Phys. 2004;31(11):2942–8. doi: 10.1118/1.1803671. - DOI - PubMed
    1. Mattes D, Haynor DR, Vesselle H, Lewellen TK, Eubank W. PET-CT image registration in the chest using free-form deformation. IEEE Trans Med Imaging. 2003;22(1):120–8. doi: 10.1109/TMI.2003.809072. - DOI - PubMed

Publication types

MeSH terms