Speeding Up Colon CAD Using KD-Tree

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 246)


This paper proposes an efficient technique to speed up our colon CAD software for flat lesion recognition in colon CT images. The proposed technique uses KD-tree to speed up the neighbor searching part in the software. We test our method under Linux system with intel(R) Xeon(R) 2.66 GHz CPU X5355, 12 G memory. Experiments on 50 computed tomographic colonography (CTC) scan database demonstrate the performance of our speeding up method based on KD-tree. It significantly reduces the average processing time from 6,134 s down to 514 s for each CTC scan.



Supported by the National Natural Science Foundation of China under Grant No.61001086 and the Fundamental Research Funds for the Central Universities Grant No. ZYGX2011X004.


  1. 1.
    Dachman AH (2003) Atlas of virtual colonoscopy. Springer, New YorkCrossRefGoogle Scholar
  2. 2.
    Ferraro F, Kawaler E, Suzuki K (2011) A spinning tangent based CAD system for detection of flat lesions in CT colonography. In: Proceedings of ISBI2011, pp 156–159Google Scholar
  3. 3.
    Suzuki K, Rockey DC, Dachman AH (2010) CT colonography: advanced computer-aided detection scheme utilizing MTANNs for detection of “missed” polyps in a multicenter clinical trial. Med Phys 37:12–21CrossRefGoogle Scholar
  4. 4.
    Ravesteijn VFV, Wijk CV, Vos FM, Truyen R, Peters JF, Stoker J, Vliet LJV (2010) Computer-aided detection of polyps in CT colonography using logistic regression. IEEE Trans Med Imag 29:120–131CrossRefGoogle Scholar
  5. 5.
    Omohundro SM (1987) Efficient algorithms with neural network behavior. Complex Syst 1:273–347MATHMathSciNetGoogle Scholar
  6. 6.
    Sanger TD (1991) A tree-structured algorithm for reducing computation in networks with separable basis functions. Neural Comput 3:67–78CrossRefGoogle Scholar
  7. 7.
    Moore AW (1991) An introductory tutorial on kd-trees. Technical Report No. 29, Computer Laboratory, Univeristy of Cambridge, pp 1–20Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.School of Electronic EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina

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