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.
References
Hayat M: Cancer Imaging Volume 2: Instrumentation and applications. Academic, New York, 2007
Hajnal JV, Hawkes DJ, Hill DL: Medical image registration. CRC, New York, 2001
Zitova B, Flusser J: Image registration methods: a survey. Image Vis Comput 21(11):977–1000, 2003
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 31(11):2942–8, 2004
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 22(1):120–8, 2003
Chen H-M, Varshney PK: Mutual information-based CT-MR brain image registration using generalized partial volume joint histogram estimation. IEEE Trans Med Imaging 22(9):1111–9, 2003
Studholme C, Drapaca C, Iordanova B, Cardenas V: Deformation-based mapping of volume change from serial brain MRI in the presence of local tissue contrast change. IEEE Trans Med Imaging 25(5):626–39, 2006
Pluim JPW, Maintz JBA, Viergever MA: Mutual-information-based registration of medical images: a survey. Med Imaging IEEE Trans 22(8):986–1004, 2003
Maes F, Vandermeulen D, Suetens P: Medical image registration using mutual information. Proc IEEE 91(10):1699–722, 2003
Peleg S, Dar G, Steinberg N, Peled N, Hershkovitz I, Masharawi Y: Sacral orientation revisited. Spine 32:E397–404, 2007
Putz R, Muller-Gerbl M: Anatomic characteristics of the pelvic girdle. Unfallchirurg 95:164–7, 1992
Tisnado J, Amendola MA, Walsh JW, Jordan RL, Turner MA, Krempa J: Computed tomography of the perineum. Am J Roentgenol 136(3):475–81, 1981
Viola P, Jones MJ: Robust real-time face detection. Int J Comput Vision 57(2):137–54, 2004
Schapire RE, Singer Y: Improved boosting algorithms using confidence-rated predictions. Mach Learn 37(3):297–336, 1999
Duda RO, Hart PE, Stork DG: Pattern classification, 2nd edition. Wiley, Chichester, 2001
Fukunaga K: Introduction to statistical pattern recognition, 2nd edition. Academic, New York, 1990
Belhumeur PN, Hespanha JP, Kriegman DJ: Eigenfaces vs Fisherfaces: recognition using class specific linear projection. IEEE Trans Pattern Anal Mach Intell 19(7):711–20, 1997
Zhou XS, Huang TS: Small sample learning during multimedia retrieval using BiasMap. Proc. of IEEE Conference on Computer Vision and Pattern Recognition, 2001
Tao D, Tang X: Kernel full-space biased discriminant analysis. Proc. IEEE Conference on Multimedia and Expo, 2004
Tao D, Tang X, Li X, Rui Y: Direct kernel biased discriminant analysis: a new content-based image retrieval relevance feedback algorithm. IEEE Trans Multimedia 8(4):716–27, 2006
Friedman JH: Regularized discriminant analysis. J Am Stat Assoc 84(405):165–75, 1989
Acknowledgment
The first and second authors were supported by the National Cancer Center (Grant No. 0910130-1), and the first and third authors have been supported by Mid-career Researcher Program through NRF grant funded by the MEST (No. 2011-0000059).
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The first (J.O) and second author (D.C.J) equally contributed to this work.
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Oh, J., Jung, D.C. & Choi, CH. Locating the Reference Point of Symphysis Pubis in Axial CT Images. J Digit Imaging 25, 110–120 (2012). https://doi.org/10.1007/s10278-011-9384-z
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DOI: https://doi.org/10.1007/s10278-011-9384-z