loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
A Pipeline for Computer Aided Polyp Detection
September-October 2006 (vol. 12 no. 5)
pp. 861-868
We present a novel pipeline for computer-aided detection (CAD) of colonic polyps by integrating texture and shape analysis with volume rendering and conformal colon flattening. Using our automatic method, the 3D polyp detection problem is converted into a 2D pattern recognition problem. The colon surface is first segmented and extracted from the CT data set of the patient's abdomen, which is then mapped to a 2D rectangle using conformal mapping. This flattened image is rendered using a direct volume rendering technique with a translucent electronic biopsy transfer function. The polyps are detected by a 2D clustering method on the flattened image. The false positives are further reduced by analyzing the volumetric shape and texture features. Compared with shape based methods, our method is much more efficient without the need of computing curvature and other shape parameters for the whole colon surface. The final detection results are stored in the 2D image, which can be easily incorporated into a virtual colonoscopy (VC) system to highlight the polyp locations. The extracted colon surface mesh can be used to accelerate the volumetric ray casting algorithm used to generate the VC endoscopic view. The proposed automatic CAD pipeline is incorporated into an interactive VC system, with a goal of helping radiologists detect polyps faster and with higher accuracy.

[1] 861 B. Acar, C. Beaulieu, S. Gokturk, C. Tomasi, D. Paik, R. B. Jeffrey, J. Yee, and S. Napel, Edge displacement field-based classification for improved detection of polyps in CT colonography. IEEE Transactions on Medical Imaging, 21: 1461–1467, 2002.[2] R. S. Avila, L. M. Sobierajski, and A. E. Kaufman, Towards a comprehensive volume visualization system. IEEE Visualization, pages 13–20, 1992.[3] A. V. Bartroli, R. Wegenkittl, A. Konig, and E. Groller, Nonlinear virtual colon unfolding. IEEE Visualization, pages 411–418, Oct. 2001.[4] G. Bertrand, Simple points, topological numbers and geodesic neighborhoods in cubic grids. Pattern Recognition Letters, 15: 1003–1011, 1994.[5] B. Cabral, N. Cam, and J. Foran, Accelerated volume rendering and tomographic reconstruction using texture mapping hardware. Symposium on Volume Visualization, pages 91–98, 1994.[6] S. B. Göktürk, C. Tomasi, B. Acar, C. F. Beaulieu, D. S. Paik, R. B. Jeffrey, J. Yee, and S. Napel, A statistical 3D pattern processing method for computer aided detection of polyps in CT colonography. IEEE Transactions on Medical Imaging, 20 (12): 1251–1260, 2001.[7] S. Haker, S. Angenent, A. Tannenbaum, and R. Kikinis, Nondistorting flattening maps and the 3D visualization of colon CT images. IEEE Transactions on Medical Imaging, 19: 665–670, Dec. 2000.[8] X. Han, C. Xu, and J. L. Prince, A topology preserving level set method for geometric deformable models. IEEE Transactions on PAMI, 25 (6): 755–768, 2003.[9] L. Hong, S. Muraki, A. Kaufman, D. Bartz, and T. He, Virtual voyage: interactive navigation in the human colon. SIGGRAPH, pages 27–34, 1997.[10] W. Hong, X. Gu, F. Qiu, M. Jin, and A. Kaufman, Conformal virtual colon flattening. ACM Symposium on Solid and Physical Modeling, pages 85–94, 2006.[11] C. D. Johnson and A. H. Dachman, CT colonography: The next colon screening examination? Radiology, 216 (2): 331–341, 2000.[12] G. Kiss, J. Cleynenbreugel, M. Thomeer, P. Suetens, and G. Marchal, Computer-aided diagnosis in virtual colonography via combination of surface normal and sphere fitting methods. European Journal of Radiology, 12: 77–81, 2002.[13] J. Kruger and R. Westermann, Acceleration techniques for GPU-based volume rendering. IEEE Visualization, pages 38–44, 2003.[14] J. S. Mandel, J. H. Bond, T. R. Church, D. C. Snover, G. M. Bradley, L. M. Schuman, and F. Ederer, Reducing mortality from colorectal cancer by screening for fecal occult blood. New England Journal of Medicine, 328 (19): 1365–1371, 1993.[15] J. Nappi, H. Frimmel, A. Dachman, and H. Yoshida, Computerized detection of colorectal masses in ct colonography based on fuzzy merging and wall-thickening analysis. Medical Physics, 31: 860–872, 2004.[16] J. Nappi and H. Yoshida, Feature-guided analysis for reduction of false positives in cad of polyps for CT colonography. Medical Physics, 30: 1592–1601, 2003.[17] D. S. Paik, C. F. Beaulieu, G. D. Rubin, B. Acar, R. B. Jeffery, J. Yee, J. Dey, and S. Napel, Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT. IEEE Transactions on Medical Imaging, 23 (6): 661–675, June 2004.[18] P. J. Pickhardt, J. R. Choi, I. Hwang, J. A. Butler, M. L. Puckett, H. A. Hildebrandt, R. K. Wong, P. A. Nugent, P. A. Mysliwiec, and W. R. Schindler, Computed tomographic virtual colonoscopy to screen for colorectal neoplasia in asymptomatic adults. The New England Journal of Medicine, 349 (23): 2191–2200, Dec. 2003.[19] R. M. Summers, C. D. Johnson, L. M. Pusanik, J. D. Malley, A. M. Youssef, and J. E. Reed, Automated polyp detection at CT colonography: Feasibility assessment in a human population. Radiology, 219 (1): 51–59, 2001.[20] C. Tomasi and S. B. Göktürk, A graph method for the conservative detection of polyps in the colon. 2nd International Symposium on Virtual Colonoscopy, 2000.[21] D. Vining, Y Ge, D. Ahn, and D. Stelts, Virtual colonoscopy with computer-assisted polyps detection. Computer-Aided Diagnosis in Medical Imaging, pages 445–452, 1999.[22] M. Wan, F. Dachille, K. Kreeger, S. Lakare, M. Sato, A. Kaufman, M. Wax, and J. Liang, Interactive electronic biopsy for 3D virtual colonoscopy. SPIE Medical Imaging, 4321: 483–488, 2001.[23] G. Wang and M. W. Vannier, GI tract unraveling by spiral CT. Proceedings SPIE, 2434: 307–315, 1995.[24] Z. Wang, Z. Liang, L. Li, X. Li, B. Li, J. Anderson, and D. Harrington, Reduction of false positives by internal features for polyp detection in CT-based virtual colonoscopy. Medical Physics, 32 (12): 3602–3616, 2005.[25] Z. Wang, Z. Liang, X. Li, L. Li, D. Eremina, and H. Lu, An improved electronic colon cleansing method for detection of colonic polyps by virtual colonoscopy. IEEE Transactions on Biomedical Engineering, 53: 1635–1646, 2006.[26] J. Yao, M. Miller, M. Franaszek, and R. Summers, Colonic polyp segmentation in CT colonoscopy-based on fuzzy clustering and deformable models. IEEE Transactions on Medical Imaging, 23: 1344–1352, 2004.[27] H. Yoshida, Y. Masutani, P. MacEneaney, D. T. Rubin, and A. H. Dachman, Computerized detection of colonic polyps in CT colonography based on volumetric features: A pilot study. Radiology, pages 327–336, Jan. 2002.[28] H. Yoshida and J. Näppi, Three-dimensional computer-aided diagnosis scheme for detection of colonic polyps. IEEE Transactions on Medical Imaging, 20 (12): 1261–1274, 2001.[29] N. Zhang, W. Hong, and A. Kaufman, Dual contouring with topolgy-preserving simplification using enhanced cell representation. IEEE Visualization, pages 505–512, Oct. 2004.

Index Terms:
Computer Aided Detection, Virtual Colonoscopy, Texture Analysis, Volume Rendering
Citation:
Wei Hong, Feng Qiu, Arie kaufman, "A Pipeline for Computer Aided Polyp Detection," IEEE Transactions on Visualization and Computer Graphics, vol. 12, no. 5, pp. 861-868, Sept. 2006, doi:10.1109/TVCG.2006.112
Usage of this product signifies your acceptance of the Terms of Use.