虚拟结肠可视化的关键技术研究：全自动分割与基于外壁的虚拟展平
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摘要
虚拟结肠可视化技术是各种关于结肠三维显示以及观察方法的总称。虚拟结肠可视化技术可以非侵入地对结肠息肉进行检测，从而用于对结肠癌的预防。医学研究发现，结肠肿瘤一般都是由结肠息肉经过数年的发展形成。所以，对结肠息肉的及时检测以及尽早切除，是降低结肠癌致死率的一种极为有效的手段。
虚拟结肠可视化技术是一个庞大的系统，包括人体数据获取、结肠数据分割、结肠中心路径计算、结肠数据可视化四个模块。为了完善虚拟结肠可视化技术，本论文将研究重点集中在结肠数据分割以及结肠数据可视化。
结肠数据分割常常受困于对比增强剂的服用和结肠充气两个问题。对比增强剂使得那些高CT值的非结肠组织（如骨骼、同样包含对比增强剂的小肠等）会很容易地被引入到结肠的分割结果中。结肠充气则常常会伴随着过度膨胀和充气不足的情况。过度膨胀会导致结肠不同区域之间的互相粘连，而充气不足会导致分割结果的断裂。为了克服对比增强剂的服用以及结肠充气导致的拓扑性分割错误，如结肠断裂、结肠粘连、非结肠组织引入等，本论文创新性地提出了一种全自动结肠数据分割方法。全自动结肠数据分割方法能够实现从输入人体腹部CT数据开始直至计算出结肠中心路径的整个过程的全自动化。全自动结肠数据分割方法由一系列崭新算法组成，包括：1)区域增长种子点的自动定位算法；2)基于单连通形态学闭运算的解剖标志点自动定位算法；3)基于最短路径的结肠片段选取算法；4)基于互补测地线距离场的结肠粘连以及非结肠组织的自动去除算法。本论文使用170个CT数据对全自动分割方法进行测试，其中133个CT数据被认为是难以自动分割的[1,2]。以人工标记的中心路径为基准，使用全自动分割方法得到的分割结果计算出来的结肠中心路径可以达到90.56%的中心路径正确覆盖率，比现有的方法至少提高了15%。
在完成结肠数据分割并且提取中心路径之后，本论文的研究重点转移至结肠数据可视化模块中的虚拟展平技术上。虚拟展平技术是一种常用的结肠数据可视化方式，它的突出优点是检测视野大、速度极快。虚拟展平技术首先沿结肠中心路径对三维结肠进行采样，然后将采样结果重建到二维平面上进行息肉检测。然而，对三维结肠的非线性采样往往会导致重建的二维结肠平面出现严重的形变，使得息肉的检出率下降，误检率上升。因此，本论文创新性地提出一种基于结肠外壁的虚拟展平方法，用于校正三维结肠的非线性采样结果，从而减轻二维结肠平面的非线性形变。基于结肠外壁的虚拟展平方法包含两个创新部分：1)改进了关于结肠外壁的提取方法；2)提出了基于结肠外壁对结肠采样结果进行校正的方法。本论文使用60个结肠数据对提出的方法进行评价。这60个结肠数据总共包含了200个已知的息肉。三个研究人员在图形工作站上对展平结果进行检测。实验结果表明基于结肠外壁的虚拟展平方法可以达到88.0%的息肉检出率，而误检率只有每个结肠数据0.16个错误息肉。
本论文实现了结肠数据的全自动分割，并且极大地改善了虚拟结肠展平技术的性能。我们相信，本论文的研究对于提高虚拟结肠可视化系统关于结肠息肉的检测性能有重要意义。
The technique of virtual colon visualization represents a large number ofthree dimensional colon display and inspection methods. Virtual colonvisualization is a kind of noninvasive procedure developed for screeningcolorectal cancer. Colorectal tumors are believed to derive from colorectalpolyps, which might take a few years to grow up before becoming cancerous. Earlydetection and successful resection of the precursor polyps can effectivelyreduce the cancer-related mortality rates.
The technique of virtual colon visualization involves a series of modules,including data acquisition, colon segmentation, colon centerline computationand colonic data visualization. In this dissertation, our work is concentratedon two of the complicated modules: colon segmentation and colonic datavisualization, so as to improve the performance of virtual colon visualization.
Two problems impede reliable colon segmentation. The first is the use oforal contrast agents for bowel preparation. Oral contrast agents could make thoseissues of high CT values, such as bones and small intestines, be easily andmistakenly included into the segmentation results. The second is the applicationof insufflations when conducting CT scanning. Insufflations could causeoverdistention/underdistention to the colon. Overdistention might produce loopsin the segmented colon, while underdistention might lead to collapse in thesegmented colon. To correct the topological errors caused by the two problems,a fully automated colon segmentation method is proposed in this dissertation.The proposed method takes advantages of colonic topological information, aimingto fully automate the process from data acquisition to colon centerlinecomputation. The proposed segmentation method contains four novel algorithms:1) automated seed placement algorithm for region growing,2)automated anatomicallandmark location algorithm based on single-connected morphological closingoperation,3) colonic segments selection algorithm based on shortest path principle and4) loop and non-colonic tissue removal algorithm based oncomplementary geodesic distance map.170CT abdominal data are used to validatethe proposed method. Computer-generated centerlines are compared tohuman-generated centerlines. The proposed method yields a90.56%correctcoverage rate with respect to the human-generated centerlines.
In the module of colonic data visualization, we focus on how to improve theperformance of the technique of virtual colon flattening. Virtual colonflattening technique is able to map the three dimensional colonic wall onto atwo dimensional surface, and thus can provide a global field of view of the entirecolonic wall on a single inspection window. Unfortunately, great distortionsof colonic wall might occur during the mapping process from three dimensionalspace to two dimensional surface, leading to missed polyps and false polypsdetection.Therefore, in this dissertation, a novel virtual colon flatteningmethod based on colonic outer surface is proposed. The proposed method is capableto adaptively correct distortions by using colonic outer surface instead ofcolonic inner surface.The proposed colonic outer surface based flattening methodis mainly composed of two parts:1) improve the algorithm for colonic outersurface extraction and2) develop a novel algorithm to correct the nonlinearityfor sampling planes based on colonic outer surface.We test the proposed methodon60colon cases which contain200annotated polyps in total. Visual inspectionsby three independent operators demonstrate that the proposed method can achieve88.0%correct dectection rate and the false detection rate is only0.16falsedetections per case.
In this dissertation, we fulfill the fully automated colon segmentation andgreatly improve the performance of virtual colon flattening. We believe thatthe proposed methods in our work would be valuable to enhance the performanceof colonic polyp detection for virtual colon visualization system.
虚拟结肠可视化技术是一个庞大的系统，包括人体数据获取、结肠数据分割、结肠中心路径计算、结肠数据可视化四个模块。为了完善虚拟结肠可视化技术，本论文将研究重点集中在结肠数据分割以及结肠数据可视化。
结肠数据分割常常受困于对比增强剂的服用和结肠充气两个问题。对比增强剂使得那些高CT值的非结肠组织（如骨骼、同样包含对比增强剂的小肠等）会很容易地被引入到结肠的分割结果中。结肠充气则常常会伴随着过度膨胀和充气不足的情况。过度膨胀会导致结肠不同区域之间的互相粘连，而充气不足会导致分割结果的断裂。为了克服对比增强剂的服用以及结肠充气导致的拓扑性分割错误，如结肠断裂、结肠粘连、非结肠组织引入等，本论文创新性地提出了一种全自动结肠数据分割方法。全自动结肠数据分割方法能够实现从输入人体腹部CT数据开始直至计算出结肠中心路径的整个过程的全自动化。全自动结肠数据分割方法由一系列崭新算法组成，包括：1)区域增长种子点的自动定位算法；2)基于单连通形态学闭运算的解剖标志点自动定位算法；3)基于最短路径的结肠片段选取算法；4)基于互补测地线距离场的结肠粘连以及非结肠组织的自动去除算法。本论文使用170个CT数据对全自动分割方法进行测试，其中133个CT数据被认为是难以自动分割的[1,2]。以人工标记的中心路径为基准，使用全自动分割方法得到的分割结果计算出来的结肠中心路径可以达到90.56%的中心路径正确覆盖率，比现有的方法至少提高了15%。
在完成结肠数据分割并且提取中心路径之后，本论文的研究重点转移至结肠数据可视化模块中的虚拟展平技术上。虚拟展平技术是一种常用的结肠数据可视化方式，它的突出优点是检测视野大、速度极快。虚拟展平技术首先沿结肠中心路径对三维结肠进行采样，然后将采样结果重建到二维平面上进行息肉检测。然而，对三维结肠的非线性采样往往会导致重建的二维结肠平面出现严重的形变，使得息肉的检出率下降，误检率上升。因此，本论文创新性地提出一种基于结肠外壁的虚拟展平方法，用于校正三维结肠的非线性采样结果，从而减轻二维结肠平面的非线性形变。基于结肠外壁的虚拟展平方法包含两个创新部分：1)改进了关于结肠外壁的提取方法；2)提出了基于结肠外壁对结肠采样结果进行校正的方法。本论文使用60个结肠数据对提出的方法进行评价。这60个结肠数据总共包含了200个已知的息肉。三个研究人员在图形工作站上对展平结果进行检测。实验结果表明基于结肠外壁的虚拟展平方法可以达到88.0%的息肉检出率，而误检率只有每个结肠数据0.16个错误息肉。
本论文实现了结肠数据的全自动分割，并且极大地改善了虚拟结肠展平技术的性能。我们相信，本论文的研究对于提高虚拟结肠可视化系统关于结肠息肉的检测性能有重要意义。
The technique of virtual colon visualization represents a large number ofthree dimensional colon display and inspection methods. Virtual colonvisualization is a kind of noninvasive procedure developed for screeningcolorectal cancer. Colorectal tumors are believed to derive from colorectalpolyps, which might take a few years to grow up before becoming cancerous. Earlydetection and successful resection of the precursor polyps can effectivelyreduce the cancer-related mortality rates.
The technique of virtual colon visualization involves a series of modules,including data acquisition, colon segmentation, colon centerline computationand colonic data visualization. In this dissertation, our work is concentratedon two of the complicated modules: colon segmentation and colonic datavisualization, so as to improve the performance of virtual colon visualization.
Two problems impede reliable colon segmentation. The first is the use oforal contrast agents for bowel preparation. Oral contrast agents could make thoseissues of high CT values, such as bones and small intestines, be easily andmistakenly included into the segmentation results. The second is the applicationof insufflations when conducting CT scanning. Insufflations could causeoverdistention/underdistention to the colon. Overdistention might produce loopsin the segmented colon, while underdistention might lead to collapse in thesegmented colon. To correct the topological errors caused by the two problems,a fully automated colon segmentation method is proposed in this dissertation.The proposed method takes advantages of colonic topological information, aimingto fully automate the process from data acquisition to colon centerlinecomputation. The proposed segmentation method contains four novel algorithms:1) automated seed placement algorithm for region growing,2)automated anatomicallandmark location algorithm based on single-connected morphological closingoperation,3) colonic segments selection algorithm based on shortest path principle and4) loop and non-colonic tissue removal algorithm based oncomplementary geodesic distance map.170CT abdominal data are used to validatethe proposed method. Computer-generated centerlines are compared tohuman-generated centerlines. The proposed method yields a90.56%correctcoverage rate with respect to the human-generated centerlines.
In the module of colonic data visualization, we focus on how to improve theperformance of the technique of virtual colon flattening. Virtual colonflattening technique is able to map the three dimensional colonic wall onto atwo dimensional surface, and thus can provide a global field of view of the entirecolonic wall on a single inspection window. Unfortunately, great distortionsof colonic wall might occur during the mapping process from three dimensionalspace to two dimensional surface, leading to missed polyps and false polypsdetection.Therefore, in this dissertation, a novel virtual colon flatteningmethod based on colonic outer surface is proposed. The proposed method is capableto adaptively correct distortions by using colonic outer surface instead ofcolonic inner surface.The proposed colonic outer surface based flattening methodis mainly composed of two parts:1) improve the algorithm for colonic outersurface extraction and2) develop a novel algorithm to correct the nonlinearityfor sampling planes based on colonic outer surface.We test the proposed methodon60colon cases which contain200annotated polyps in total. Visual inspectionsby three independent operators demonstrate that the proposed method can achieve88.0%correct dectection rate and the false detection rate is only0.16falsedetections per case.
In this dissertation, we fulfill the fully automated colon segmentation andgreatly improve the performance of virtual colon flattening. We believe thatthe proposed methods in our work would be valuable to enhance the performanceof colonic polyp detection for virtual colon visualization system.
引文
[1] J. Nappi, A. Okamura, H. Frimmel, A. Dachman, and H. Yoshida, Region-based supine-pronecorrespondence for the reduction of false-positive CAD polyp candidates in CT colonography. AcadRadiol,2005.12(6): p.695-707.
[2] J. Nappi and H. Yoshida, Fully automated three-dimensional detection of polyps in fecal-tagging CTcolonography. Acad Radiol,2007.14(3): p.287-300.
[3] A. Vesalius, De Humani Corporis Fabrica.1543, BASILE AE: EX OFFICI.
[4] K.H. Hoehne, VOXEL-MAN3D-Navigator: Inner Organs. Regional, Systemic and RadiologicalAnatomy.2003, New York: Springer Electronic Media.
[5] C.A. Pickover, Frontiers of Scientific Visualization.1994: Wiley.
[6] L.Rosenblum, R.A. Earnshaw, J. Encarnacao, H. Hagen, A. Kaufaman, S. Klimenko, G. Nielson, F. Post,and D. Thalmann, Scientific Visualization Advances and Challenges.1994: IEEE Computer Society.
[7] D.J. Vining and D.W. Gelfand, Noninvasive colonoscopy using helical CT scanning,3D reconstruction,and virtual reality, in23rd Annual Meeting, Society of Gastrointestinal Radiologists.1994: Maui.
[8] D.J. Vining, R.Y. Shifrin, E.K. Grishaw, and A.R. Padhani. Virtual reality imaging of human anatomy.Computer Applications to Assist Radiology.1994. Carlsbad, CA: Symposia Foundation.
[9] D.J. Vining, D.W. Gelfand, R.E. Bechtold, E. Scharling, E. Grishaw, and R. Shifrin, Technical feasibilityof colon imaging with helical CT and virtual reality. AJR Am J Roentgenol,1994.1(162): p.104-108.
[10] E. Neri, D. Caramella, and C. Bartolozzi, Image Processing in Radiology-Current Applications.2006:Springer Berlin Heidelberg New York.
[11] A.Y. Kim, H.J. Kim, and H.K. Ha, Gastric cancer by multidetector row CT: preoperative staging. AbdomImaging,2005.30(4): p.465-472.
[12] H. Alkadhi, S. Wildermuth, B. Marincek, and T. Boehm, Accuracy and time efficiency for the detection ofthoracic cage fractures: volume rendering compared with transverse computed tomography images. JComput Assist Tomography,2004.3(28): p.378-385.
[13] S. Men, M.C. Ecevit, I. Topcu, N. Kabakci, T.K. Erdag, and S. Sutay, Diagnostic contribution of virtualendoscopy in diseases of the upper airways. J Digit Imaging,2007.20(1): p.67-71.
[14] K.D. Hopper, A.T. Iyriboz, S.W. Wise, and J.A. Fornadley, The feasibility of surgical site tagging with CTvirtual reality of the paranasal sinuses. J Comput Assist Tomogr,1999.23(4): p.529-33.
[15] P. Prassopoulos, N. Papanikolaou, T. Maris, C. Gogas, J. Mouzas, and N. Gourtsoyiannis, Developmentof contrast-enhanced virtual MR cholangioscopy: a feasibility study. Eur Radiol,2002.12(6): p.1438-41.
[16] H.M. Fenlon, D.P. Nunes, P.C. Schroy,3rd, M.A. Barish, P.D. Clarke, and J.T. Ferrucci, A comparison ofvirtual and conventional colonoscopy for the detection of colorectal polyps. N Engl J Med,1999.341(20):p.1496-503.
[17] 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 colorectalneoplasia in asymptomatic adults. N Engl J Med,2003.349(23): p.191-200.
[18] D. Regge, C. Hassan, P.J. Pickhardt, A. Laghi, A. Zullo, D.H. Kim, F. Iafrate, and S. Morini, Impact ofcomputer-aided detection on the cost-effectiveness of CT colonography. Radiology,2009.250(2): p.488-97.
[19] A. Jemal, T. Murray, A. Samuels, A. Ghafoor, E. Ward, and M.J. Thun, Cancer statistics,2003. CA CancerJ Clin,2003.53(1): p.5-26.
[20] A. Jemal, R.C. Tiwari, T. Murray, A. Ghafoor, A. Samuels, E. Ward, E.J. Feuer, and M.J. Thun, Cancerstatistics,2004. CA Cancer J Clin,2004.54(1): p.8-29.
[21] A. Jemal, T. Murray, E. Ward, A. Samuels, R.C. Tiwari, A. Ghafoor, E.J. Feuer, and M.J. Thun, Cancerstatistics,2005. CA Cancer J Clin,2005.55(1): p.10-30.
[22] A. Jemal, R. Siegel, E. Ward, T. Murray, J. Xu, C. Smigal, and M.J. Thun, Cancer statistics,2006. CACancer J Clin,2006.56(2): p.106-30.
[23] A. Jemal, R. Siegel, E. Ward, T. Murray, J. Xu, and M.J. Thun, Cancer statistics,2007. CA Cancer J Clin,2007.57(1): p.43-66.
[24] A. Jemal, R. Siegel, E. Ward, Y. Hao, J. Xu, T. Murray, and M.J. Thun, Cancer statistics,2008. CA CancerJ Clin,2008.58(2): p.71-96.
[25] A. Jemal, R. Siegel, E. Ward, Y. Hao, J. Xu, and M.J. Thun, Cancer statistics,2009. CA Cancer J Clin,2009.59(4): p.225-49.
[26] A. Jemal, R. Siegel, J. Xu, and E. Ward, Cancer statistics,2010. CA Cancer J Clin,2010.60(5): p.277-300.
[27] R. Siegel, E. Ward, O. Brawley, and A. Jemal, Cancer statistics,2011: the impact of eliminatingsocioeconomic and racial disparities on premature cancer deaths. CA Cancer J Clin,2011.61(4): p.212-36.
[28] R. Siegel, D. Naishadham, and A. Jemal, Cancer statistics,2012. CA Cancer J Clin,2012.62(1): p.10-29.
[29] R. Siegel, D. Naishadham, and A. Jemal, Cancer statistics,2013. CA Cancer J Clin,2013.
[30] J.H. Bond, Clinical evidence for the adenoma-carcinoma sequence, and the management of patients withcolorectal adenomas. Semin Gastrointest Dis,2000.11(4): p.176-84.
[31] J.H. Bond, Colon polyps and cancer. Endoscopy,2005.37(3): p.208-12.
[32] M.J. O'Brien, S.J. Winawer, A.G. Zauber, L.S. Gottlieb, S.S. Sternberg, B. Diaz, G.R. Dickersin, S.Ewing, S. Geller, D. Kasimian, and et al., The National Polyp Study. Patient and polyp characteristicsassociated with high-grade dysplasia in colorectal adenomas. Gastroenterology,1990.98(2): p.371-379.
[33] G. Wang, E. McFarland, B.P. Brown, and M.W. Vannier, GI tract unraveling with curved cross-sections.IEEE Trans Med Imaging,1998.17(2): p.318-322.
[34] B. Geiger, C. Chefd, and S. Sudarsky, Panoramic views for virtual endoscopy. Med Image ComputComput Assist Interv,2005.8(Pt1): p.662-669.
[35] J. Zhao, L. Cao, T. Zhuang, and G. Wang, Digital eversion of a hollow structure: an application in virtualcolonography. Int J Biomed Imaging,2008.
[36] M.S. Hassouna, A.A. Farag, and R. Falk, Virtual fly-over: a new visualization technique for virtualcolonoscopy. Med Image Comput Comput Assist Interv,2006.9(Pt1): p.381-8.
[37] S.S. Lee, S.H. Park, J.K. Kim, N. Kim, J. Lee, B.J. Park, Y.J. Kim, M.W. Lee, A.Y. Kim, and H.K. Ha,Panoramic endoluminal display with minimal image distortion using circumferential radial ray-casting forprimary three-dimensional interpretation of CT colonography. Eur Radiol,2009.19(8): p.1951-1960.
[38] R.C. Gonzalez,数字图像处理（第二版）（Digital Image Processing, Second Edition）.2003.3:电子工业出版社.
[39] J. Bouttier, P.D. Francesco, and E. Guitter, Geodesic distance in planar graphs. Nucl Phys,2003.3(663): p.368-374.
[40] D.G. Kang, D.C. Suh, and J.B. Ra, Three-dimensional blood vessel quantification via centerlinedeformation. IEEE Trans Med Imaging,2009.28(3): p.405-419.
[41] S. Osher and J. Sethian, Fronts propagating with curvature-dependent speed: Algorithms based onHamilton-Jacobi formulations. Comput. Phys.,1988(79): p.12-49.
[42] J.K. Udupa and P.K. Saha, Fuzzy connectedness and image segmentation. Proceedings of the IEEE,2003.91(10): p.1649-1669.
[43] H. Blum, Biological shape and visual science. J Theor Biol,1973.2(38): p.205-293.
[44] C.M. Ma and M. Sonka, A Fully Parallel3D Thinning Algorithm and Its Applications. Comput Vis ImageUnderst,1996.3(64): p.420-433.
[45] Y. Zhou, A. Kaufman, and A.W. Toga, Three-Dimensional Skeleton and Centerline Generation Based onan Approximate Maximum Distance Field.1998(14): p.303-314.
[46] I. Bitter, M. Sato, A. Kaufman, and M. Wan. CEASAR: A Smooth, Accurate and Robust CenterlineExtraction Algorithm. IEEE Visualization.2000.
[47] G. Lohmann, Volumetric Image Analysis.1998: Chichester Wiley.
[48] C.M. Ma and S.Y. Wan, Parallel thinning algorithms on3D binary images. Comput Vis Image Underst,2000.3(80): p.364-380.
[49] E.W. Dijkstra, A note on two problems in connexion with graphs.1959: Numerische Mathematik1.269-271.
[50] M.S. Juchems, A. Ernst, P. Johnson, S. Virmani, H.J. Brambs, and A.J. Aschoff, Electroniccolon-cleansing for CT colonography: diagnostic performance. Abdom Imaging,2009.34(3): p.359-364.
[51] B.C. Pineau, E.D. Paskett, G.J. Chen, M.A. Espeland, K. Phillips, J.P. Han, C. Mikulaninec, and D.J.Vining, Virtual colonoscopy using oral contrast compared with colonoscopy for the detection of patientswith colorectal polyps. Gastroenterology,2003.125(2): p.304-310.
[52]吴东,不同对比剂用于螺旋CT胃部三维成像的对照研究.中华放射学杂志,2001.35(4): p.258-261.
[53]余深平,大肠充气螺旋CT扫描图像后处理功能的临床应用.中华放射学杂志,2000.34(5): p.295-299.
[54] A. Souza, J.K. Udupa, and P.K. Saha, Volume rendering in the presence of partial volume effects. IEEETrans Med Imaging,2005.24(2): p.223-235.
[55] A. Zhou, H. Murillo, and Q. Peng, Impact of partial volume effects on visceral adipose tissuequantification using MRI. J Magn Reson Imaging,2011.34(6): p.1452-1457.
[56] R.L.V. Uitert and R. M.Summers, Automatic correction of level set based subvoxel precise centerlines forvirtual colonoscopy using the colon outer wall. IEEE Trans Med Imaging,2007.26(8): p.1069-1078.
[57] H. Frimmel, J. Nappi, and H. Yoshida, Centerline-based colon segmentation for CT colonography. MedPhys,2005.32(8): p.2665-2672.
[58] Z. Wang, X. Li, L. Li, B. Li, D. Eremina, H. Lu, and Z. Liang, An improved electronic colon cleansingmethod for detection of polyps by virtual colonoscopy. Conf Proc IEEE Eng Med Biol Soc,2005.6: p.6512-6515.
[59] M.E. Zalis, J.J. Perumpillichira, J.Y. Kim, C. Del Frate, C. Magee, and P.F. Hahn, Polyp size at CTcolonography after electronic subtraction cleansing in an anthropomorphic colon phantom. Radiology,2005.236(1): p.118-124.
[60] M. Sezgin and B. Sankur, Survey over image thresholding techniques and quantitative performanceevaluation. J Electron Imaging,2004.13(1): p.146-168.
[61] D. Chen, Z. Liang, M.R. Wax, L. Li, B. Li, and A.E. Kaufman, A novel approach to extract colon lumenfrom CT images for virtual colonoscopy. IEEE Trans Med Imaging,2000.19(12): p.1220-1226.
[62] Z. Wang, Z. Liang, X. Li, L. Li, B. Li, D. Eremina, and H. Lu, An improved electronic colon cleansingmethod for detection of colonic polyps by virtual colonoscopy. IEEE Trans Biomed Eng,2006.53(8): p.1635-46.
[63] M.E. Zalis, J. Perumpillichira, and P.F. Hahn, Digital subtraction bowel cleansing for CT colonographyusing morphological and linear filtration methods. IEEE Trans Med Imaging,2004.23(11): p.1335-1343.
[64] I.W. Serlie, F.M. Vos, R. Truyen, F.H. Post, and L.J. van Vliet, Classifying CT image data into materialfractions by a scale and rotation invariant edge model. IEEE Trans Image Process,2007.16(12): p.2891-904.
[65] M. Franaszek, R.M. Summers, P.J. Pickhardt, and J.R. Choi, Hybrid segmentation of colon filled with airand opacified fluid for CT colonography. IEEE Trans Med Imaging,2006.25(3): p.358-68.
[66] Z. Wang, Z. Liang, X. Li, L. Li, B. Li, D. Eremina, and H. Lu, An improved electronic colon cleansingmethod for detection of colonic polyps by virtual colonoscopy. IEEE Trans Biomed Eng,2006.53(8): p.1635-1646.
[67] I.W. Serlie, F.M. Vos, R. Truyen, F.H. Post, and L.J. van Vliet, Classifying CT image data into materialfractions by a scale and rotation invariant edge model. IEEE Trans Image Process,2007.16(12): p.2891-2904.
[68] M. Franaszek, R.M. Summers, P.J. Pickhardt, and J.R. Choi, Hybrid segmentation of colon filled with airand opacified fluid for CT colonography. IEEE Trans Med Imaging,2006.25(3): p.358-368.
[69] L. Ibanez and W. Schroeder, The ITK Software Guide.2003: Kitware.
[70] T.A. Chowdhury, P.F. Whelan, and O. Ghita, A fully automatic CAD-CTC system based on curvatureanalysis for standard and low-dose CT data. IEEE Trans Biomed Eng,2008.55(3): p.888-901.
[71] V. Caselles, R. Kimmel, and G. Sapiro, Geodesic active contours. International Journal of ComputerVision,1997.1(22): p.61-80.
[72] L. Lu, M. Wolf, J. Liang, M. Dundar, J. Bi, and M. Salganicoff, A two-level approach towards semanticcolon segmentation: removing extra-colonic findings. Med Image Comput Comput Assist Interv,2009.12(Pt2): p.1009-1016.
[73] L. Lu, An automatic colon cleansing method for virtual colonoscopy.2009First International Conferenceon Information Science and Engineering,2009p. icise, pp.1129-1132.
[74] https://imaging.nci.nih.gov/ncia.
[75] A.C. Silva, C.V. Wellnitz, and A.K. Hara, Three-dimensional virtual dissection at CT colonography:unraveling the colon to search for lesions. Radiographics,2006.26(6): p.1669-86.
[76] A.V. Bartroli, R. Wegenkittl, A. Konig, E. Groller, and E. Sorantin, Virtual colon flattening. DataVisualization2001,2001: p.127-364.
[77] W. Hong, X. Gu, F. Qiu, M. Jin, and A. kaufman, Conformal virtual colon flattening. Proceedings of the2006ACM symposium on Solid and physical modeling,2006: p.85-93.
[78] W. Hong, F. Qiu, and A. Kaufman, A pipeline for computer aided polyp detection. IEEE Trans VisComput Graph,2006.12(5): p.861-868.
[79] S. Haker, S. Angenent, A. Tannenbaum, and R. Kikinis, Nondistorting flattening maps and the3-Dvisualization of colon CT images. IEEE Trans Med Imaging,2000.19(7): p.665-670.
[80] W. Zeng, J. Marino, K. Chaitanya Gurijala, X. Gu, and A. Kaufman, Supine and prone colon registrationusing quasi-conformal mapping. IEEE Trans Vis Comput Graph,2010.16(6): p.1348-1357.
[81] S. Sudarsky, B. Geiger, C. Chefd'hotel, and L. Guendel, Colon unfolding via skeletal subspacedeformation. Med Image Comput Comput Assist Interv,2008.11(Pt2): p.205-212.
[82] J. Yao, A.S. Chowdhury, J. Aman, and R.M. Summers, Reversible projection technique for colonunfolding. IEEE Trans Biomed Eng,2010.57(12): p.2861-2869.
[83] D.S. Paik, C.F. Beaulieu, R.B. Jeffrey, Jr., C.A. Karadi, and S. Napel, Visualization modes for CTcolonography using cylindrical and planar map projections. J Comput Assist Tomogr,2000.24(2): p.179-188.
[84] K.T. Johnson, J.G. Fletcher, and C.D. Johnson, Computer-aided detection (CAD) using360degree virtualdissection: can CAD in a first reviewer paradigm be a reliable substitute for primary2D or3D search?Am J Roentgenol,2007.189(4): p.172-176.
[85] A.V. Bartroli, R. Wegenkittl, A. Konig, E. Groller, and E. Sorantin, Virtual colon flattening. DataVisualization2001,2001: p.127-140.
[86] A.C. Silva, C.V. Wellnitz, and A.K. Hara, Three-dimensional virtual dissection at CT colonography:unraveling the colon to search for lesions. Radiographics,2006.26(6): p.1669-1686.
[87] Z. Zhang, G. Wang, B.P. Brown, E.G. McFarland, J. Haller, and M.W. Vannier, Fast algorithm for softstraightening of the colon. Acad Radiol,2000.7(3): p.142-148.
[88] Z. Zhang, G. Wang, B.P. Brown, and M.W. Vannier, Distortion reduction for fast soft straightening of thecolon. Acad Radiol,2000.7(7): p.506-515.
[89] M.S. Hassouna, A.A. Farag, and R. Falk, Virtual fly-over: a new visualization technique for virtualcolonoscopy. Med Image Comput Comput Assist Interv,2006.9(Pt1): p.381-389.
[90] B.S. Shin, S. Lim, and H.J. Lee, Efficient unfolding of virtual endoscopy using linear ray interpolation.Comput Methods Programs Biomed,2009.93(2): p.174-184.
[91] D. Williams, S. Grimm, E. Coto, A. Roudsari, and H. Hatzakis, Volumetric Curved Planar Reformationfor virtual endoscopy. IEEE Trans Vis Comput Graph,2008.14(1): p.109-119.
[92] P. Carrascosa, C. Capunay, E.M. Lopez, M. Ulla, R. Castiglioni, and J. Carrascosa, Multidetector CTcolonoscopy: evaluation of the perspective-filet view virtual colon dissection technique for the detectionof elevated lesions. Abdom Imaging,2007.32(5): p.582-588.
[93] P. Carrascosa, E.M. Lopez, C. Capunay, J. Vallejos, and J. Carrascosa, Virtual colonoscopy in paediatricpatients Usefulness of a colon dissection technique. Eur J Radiol,2010.74(1): p.189-194.
[94] H. Hoppe, C. Quattropani, A. Spreng, J. Mattich, P. Netzer, and H.P. Dinkel, Virtual colon dissection withCT colonography compared with axial interpretation and conventional colonoscopy: preliminary results.AJR Am J Roentgenol,2004.182(5): p.1151-1158.
[95] S.H. Kim, J.M. Lee, H.W. Eun, M.W. Lee, J.K. Han, J.Y. Lee, and B.I. Choi, Two-versusthree-dimensional colon evaluation with recently developed virtual dissection software for CTcolonography. Radiology,2007.244(3): p.852-864.
[96] H. Ray, D. Silver, H. Pfister, and T. Cook, Ray casting architectures for volume visualization. IEEE TransVis Comput Graph,1999.5(3): p.210-223.
[97] J. Lewis, M. Cordner, and N. Fong. Pose Space Deformations: A Unified Approach to Shape Interpolationand Skeleton-Driven Deformation. Proceedings of ACM SIGGRAPH.2000.
[98] S. Haker, S. Angenent, A. Tannenbaum, R. Kikinis, G. Sapiro, and M. Halle, Conformal surfaceparameterization for texture mapping. IEEE Trans Vis Comput Graph,2000.6(2): p.181-189.
[99] F. Qiu, Z. Fan, X. Yin, A. kaufman, and X. Gu, Colon Flattening with Discrete Ricci Flow. MICCAIworkshop,2008: p.97-102.
[100] L. Lu and J. Zhao, An improved method of automatic colon segmentation for virtual colon unfolding.Comput Methods Programs Biomed,2013.109(1): p.1-12.
[101] V. Caselles, R. Kimmel, and G. Sapiro, Geodesic active contour. Int J Comput Vis,1997.22(1): p.61-79.
[102] D. Zhang, J. Zhao, and L. Lu, Virtual Eversion of Colon Based Outer-Surface Centerline, in YangtzeRiver2009International Congress on Medical Imaging Physics.2009: NanJing, China. p.194-201.
[103]陈维桓,微分几何.2006,北京:北京大学出版社.
[104] S. Sudarsky, B. Geiger, C. Chefd'hotel, and L. Guendel, Colon unfolding via skeletal subspacedeformation. Med Image Comput Comput Assist Interv,2008.11(Pt2): p.205-12.
[105] Z. Wang, Z. Liang, L. Li, J. Anderson, and D. Harringtion, Reduction of False Positives by InternalFeatures for Polyp Detection in CT-Based Virtual Colonoscopy. Med Phys.,2005.12(32): p.3602-3616.
[106] B.J. Qumseya and M.B. Wallace, Advanced colorectal polyp detection techniques. Curr GastroenterolRep,2012.14(5): p.414-420.
[107] S.Y. Park, D. Sargent, I. Spofford, K.G. Vosburgh, and A.R. Y, A colon video analysis framework forpolyp detection. IEEE Trans Biomed Eng,2012.59(5): p.1408-1418.
[108] J.G. Lee, J. Hyo Kim, S. Hyung Kim, H. Sun Park, and B. Ihn Choi, A straightforward approach tocomputer-aided polyp detection using a polyp-specific volumetric feature in CT colonography. ComputBiol Med,2011.41(9): p.790-801.
[109] P.N. Figueiredo, I.N. Figueiredo, S. Prasath, and R. Tsai, Automatic polyp detection in pillcam colon2capsule images and videos: preliminary feasibility report. Diagn Ther Endosc,2011.
[110] J.L.Ong and A.K.Seghouane, From Point to Local Neighborhood: Polyp Detection in CT ColonographyUsing Geodesic Ring Neighborhoods. IEEE Trans Image Process,2011.20(4): p.1000-1010.
[111] V.F.Ravesteijn, C.Wijk, F.Vos, R.Truyen, J.F.Peters, J.Stoker, and L. J.Vliet, Computer Aided Detection ofPolyps in CT Colonography Using Logistic Regression. IEEE Trans Image Process,2010.29(1): p.120-131.
[2] J. Nappi and H. Yoshida, Fully automated three-dimensional detection of polyps in fecal-tagging CTcolonography. Acad Radiol,2007.14(3): p.287-300.
[3] A. Vesalius, De Humani Corporis Fabrica.1543, BASILE AE: EX OFFICI.
[4] K.H. Hoehne, VOXEL-MAN3D-Navigator: Inner Organs. Regional, Systemic and RadiologicalAnatomy.2003, New York: Springer Electronic Media.
[5] C.A. Pickover, Frontiers of Scientific Visualization.1994: Wiley.
[6] L.Rosenblum, R.A. Earnshaw, J. Encarnacao, H. Hagen, A. Kaufaman, S. Klimenko, G. Nielson, F. Post,and D. Thalmann, Scientific Visualization Advances and Challenges.1994: IEEE Computer Society.
[7] D.J. Vining and D.W. Gelfand, Noninvasive colonoscopy using helical CT scanning,3D reconstruction,and virtual reality, in23rd Annual Meeting, Society of Gastrointestinal Radiologists.1994: Maui.
[8] D.J. Vining, R.Y. Shifrin, E.K. Grishaw, and A.R. Padhani. Virtual reality imaging of human anatomy.Computer Applications to Assist Radiology.1994. Carlsbad, CA: Symposia Foundation.
[9] D.J. Vining, D.W. Gelfand, R.E. Bechtold, E. Scharling, E. Grishaw, and R. Shifrin, Technical feasibilityof colon imaging with helical CT and virtual reality. AJR Am J Roentgenol,1994.1(162): p.104-108.
[10] E. Neri, D. Caramella, and C. Bartolozzi, Image Processing in Radiology-Current Applications.2006:Springer Berlin Heidelberg New York.
[11] A.Y. Kim, H.J. Kim, and H.K. Ha, Gastric cancer by multidetector row CT: preoperative staging. AbdomImaging,2005.30(4): p.465-472.
[12] H. Alkadhi, S. Wildermuth, B. Marincek, and T. Boehm, Accuracy and time efficiency for the detection ofthoracic cage fractures: volume rendering compared with transverse computed tomography images. JComput Assist Tomography,2004.3(28): p.378-385.
[13] S. Men, M.C. Ecevit, I. Topcu, N. Kabakci, T.K. Erdag, and S. Sutay, Diagnostic contribution of virtualendoscopy in diseases of the upper airways. J Digit Imaging,2007.20(1): p.67-71.
[14] K.D. Hopper, A.T. Iyriboz, S.W. Wise, and J.A. Fornadley, The feasibility of surgical site tagging with CTvirtual reality of the paranasal sinuses. J Comput Assist Tomogr,1999.23(4): p.529-33.
[15] P. Prassopoulos, N. Papanikolaou, T. Maris, C. Gogas, J. Mouzas, and N. Gourtsoyiannis, Developmentof contrast-enhanced virtual MR cholangioscopy: a feasibility study. Eur Radiol,2002.12(6): p.1438-41.
[16] H.M. Fenlon, D.P. Nunes, P.C. Schroy,3rd, M.A. Barish, P.D. Clarke, and J.T. Ferrucci, A comparison ofvirtual and conventional colonoscopy for the detection of colorectal polyps. N Engl J Med,1999.341(20):p.1496-503.
[17] 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 colorectalneoplasia in asymptomatic adults. N Engl J Med,2003.349(23): p.191-200.
[18] D. Regge, C. Hassan, P.J. Pickhardt, A. Laghi, A. Zullo, D.H. Kim, F. Iafrate, and S. Morini, Impact ofcomputer-aided detection on the cost-effectiveness of CT colonography. Radiology,2009.250(2): p.488-97.
[19] A. Jemal, T. Murray, A. Samuels, A. Ghafoor, E. Ward, and M.J. Thun, Cancer statistics,2003. CA CancerJ Clin,2003.53(1): p.5-26.
[20] A. Jemal, R.C. Tiwari, T. Murray, A. Ghafoor, A. Samuels, E. Ward, E.J. Feuer, and M.J. Thun, Cancerstatistics,2004. CA Cancer J Clin,2004.54(1): p.8-29.
[21] A. Jemal, T. Murray, E. Ward, A. Samuels, R.C. Tiwari, A. Ghafoor, E.J. Feuer, and M.J. Thun, Cancerstatistics,2005. CA Cancer J Clin,2005.55(1): p.10-30.
[22] A. Jemal, R. Siegel, E. Ward, T. Murray, J. Xu, C. Smigal, and M.J. Thun, Cancer statistics,2006. CACancer J Clin,2006.56(2): p.106-30.
[23] A. Jemal, R. Siegel, E. Ward, T. Murray, J. Xu, and M.J. Thun, Cancer statistics,2007. CA Cancer J Clin,2007.57(1): p.43-66.
[24] A. Jemal, R. Siegel, E. Ward, Y. Hao, J. Xu, T. Murray, and M.J. Thun, Cancer statistics,2008. CA CancerJ Clin,2008.58(2): p.71-96.
[25] A. Jemal, R. Siegel, E. Ward, Y. Hao, J. Xu, and M.J. Thun, Cancer statistics,2009. CA Cancer J Clin,2009.59(4): p.225-49.
[26] A. Jemal, R. Siegel, J. Xu, and E. Ward, Cancer statistics,2010. CA Cancer J Clin,2010.60(5): p.277-300.
[27] R. Siegel, E. Ward, O. Brawley, and A. Jemal, Cancer statistics,2011: the impact of eliminatingsocioeconomic and racial disparities on premature cancer deaths. CA Cancer J Clin,2011.61(4): p.212-36.
[28] R. Siegel, D. Naishadham, and A. Jemal, Cancer statistics,2012. CA Cancer J Clin,2012.62(1): p.10-29.
[29] R. Siegel, D. Naishadham, and A. Jemal, Cancer statistics,2013. CA Cancer J Clin,2013.
[30] J.H. Bond, Clinical evidence for the adenoma-carcinoma sequence, and the management of patients withcolorectal adenomas. Semin Gastrointest Dis,2000.11(4): p.176-84.
[31] J.H. Bond, Colon polyps and cancer. Endoscopy,2005.37(3): p.208-12.
[32] M.J. O'Brien, S.J. Winawer, A.G. Zauber, L.S. Gottlieb, S.S. Sternberg, B. Diaz, G.R. Dickersin, S.Ewing, S. Geller, D. Kasimian, and et al., The National Polyp Study. Patient and polyp characteristicsassociated with high-grade dysplasia in colorectal adenomas. Gastroenterology,1990.98(2): p.371-379.
[33] G. Wang, E. McFarland, B.P. Brown, and M.W. Vannier, GI tract unraveling with curved cross-sections.IEEE Trans Med Imaging,1998.17(2): p.318-322.
[34] B. Geiger, C. Chefd, and S. Sudarsky, Panoramic views for virtual endoscopy. Med Image ComputComput Assist Interv,2005.8(Pt1): p.662-669.
[35] J. Zhao, L. Cao, T. Zhuang, and G. Wang, Digital eversion of a hollow structure: an application in virtualcolonography. Int J Biomed Imaging,2008.
[36] M.S. Hassouna, A.A. Farag, and R. Falk, Virtual fly-over: a new visualization technique for virtualcolonoscopy. Med Image Comput Comput Assist Interv,2006.9(Pt1): p.381-8.
[37] S.S. Lee, S.H. Park, J.K. Kim, N. Kim, J. Lee, B.J. Park, Y.J. Kim, M.W. Lee, A.Y. Kim, and H.K. Ha,Panoramic endoluminal display with minimal image distortion using circumferential radial ray-casting forprimary three-dimensional interpretation of CT colonography. Eur Radiol,2009.19(8): p.1951-1960.
[38] R.C. Gonzalez,数字图像处理（第二版）（Digital Image Processing, Second Edition）.2003.3:电子工业出版社.
[39] J. Bouttier, P.D. Francesco, and E. Guitter, Geodesic distance in planar graphs. Nucl Phys,2003.3(663): p.368-374.
[40] D.G. Kang, D.C. Suh, and J.B. Ra, Three-dimensional blood vessel quantification via centerlinedeformation. IEEE Trans Med Imaging,2009.28(3): p.405-419.
[41] S. Osher and J. Sethian, Fronts propagating with curvature-dependent speed: Algorithms based onHamilton-Jacobi formulations. Comput. Phys.,1988(79): p.12-49.
[42] J.K. Udupa and P.K. Saha, Fuzzy connectedness and image segmentation. Proceedings of the IEEE,2003.91(10): p.1649-1669.
[43] H. Blum, Biological shape and visual science. J Theor Biol,1973.2(38): p.205-293.
[44] C.M. Ma and M. Sonka, A Fully Parallel3D Thinning Algorithm and Its Applications. Comput Vis ImageUnderst,1996.3(64): p.420-433.
[45] Y. Zhou, A. Kaufman, and A.W. Toga, Three-Dimensional Skeleton and Centerline Generation Based onan Approximate Maximum Distance Field.1998(14): p.303-314.
[46] I. Bitter, M. Sato, A. Kaufman, and M. Wan. CEASAR: A Smooth, Accurate and Robust CenterlineExtraction Algorithm. IEEE Visualization.2000.
[47] G. Lohmann, Volumetric Image Analysis.1998: Chichester Wiley.
[48] C.M. Ma and S.Y. Wan, Parallel thinning algorithms on3D binary images. Comput Vis Image Underst,2000.3(80): p.364-380.
[49] E.W. Dijkstra, A note on two problems in connexion with graphs.1959: Numerische Mathematik1.269-271.
[50] M.S. Juchems, A. Ernst, P. Johnson, S. Virmani, H.J. Brambs, and A.J. Aschoff, Electroniccolon-cleansing for CT colonography: diagnostic performance. Abdom Imaging,2009.34(3): p.359-364.
[51] B.C. Pineau, E.D. Paskett, G.J. Chen, M.A. Espeland, K. Phillips, J.P. Han, C. Mikulaninec, and D.J.Vining, Virtual colonoscopy using oral contrast compared with colonoscopy for the detection of patientswith colorectal polyps. Gastroenterology,2003.125(2): p.304-310.
[52]吴东,不同对比剂用于螺旋CT胃部三维成像的对照研究.中华放射学杂志,2001.35(4): p.258-261.
[53]余深平,大肠充气螺旋CT扫描图像后处理功能的临床应用.中华放射学杂志,2000.34(5): p.295-299.
[54] A. Souza, J.K. Udupa, and P.K. Saha, Volume rendering in the presence of partial volume effects. IEEETrans Med Imaging,2005.24(2): p.223-235.
[55] A. Zhou, H. Murillo, and Q. Peng, Impact of partial volume effects on visceral adipose tissuequantification using MRI. J Magn Reson Imaging,2011.34(6): p.1452-1457.
[56] R.L.V. Uitert and R. M.Summers, Automatic correction of level set based subvoxel precise centerlines forvirtual colonoscopy using the colon outer wall. IEEE Trans Med Imaging,2007.26(8): p.1069-1078.
[57] H. Frimmel, J. Nappi, and H. Yoshida, Centerline-based colon segmentation for CT colonography. MedPhys,2005.32(8): p.2665-2672.
[58] Z. Wang, X. Li, L. Li, B. Li, D. Eremina, H. Lu, and Z. Liang, An improved electronic colon cleansingmethod for detection of polyps by virtual colonoscopy. Conf Proc IEEE Eng Med Biol Soc,2005.6: p.6512-6515.
[59] M.E. Zalis, J.J. Perumpillichira, J.Y. Kim, C. Del Frate, C. Magee, and P.F. Hahn, Polyp size at CTcolonography after electronic subtraction cleansing in an anthropomorphic colon phantom. Radiology,2005.236(1): p.118-124.
[60] M. Sezgin and B. Sankur, Survey over image thresholding techniques and quantitative performanceevaluation. J Electron Imaging,2004.13(1): p.146-168.
[61] D. Chen, Z. Liang, M.R. Wax, L. Li, B. Li, and A.E. Kaufman, A novel approach to extract colon lumenfrom CT images for virtual colonoscopy. IEEE Trans Med Imaging,2000.19(12): p.1220-1226.
[62] Z. Wang, Z. Liang, X. Li, L. Li, B. Li, D. Eremina, and H. Lu, An improved electronic colon cleansingmethod for detection of colonic polyps by virtual colonoscopy. IEEE Trans Biomed Eng,2006.53(8): p.1635-46.
[63] M.E. Zalis, J. Perumpillichira, and P.F. Hahn, Digital subtraction bowel cleansing for CT colonographyusing morphological and linear filtration methods. IEEE Trans Med Imaging,2004.23(11): p.1335-1343.
[64] I.W. Serlie, F.M. Vos, R. Truyen, F.H. Post, and L.J. van Vliet, Classifying CT image data into materialfractions by a scale and rotation invariant edge model. IEEE Trans Image Process,2007.16(12): p.2891-904.
[65] M. Franaszek, R.M. Summers, P.J. Pickhardt, and J.R. Choi, Hybrid segmentation of colon filled with airand opacified fluid for CT colonography. IEEE Trans Med Imaging,2006.25(3): p.358-68.
[66] Z. Wang, Z. Liang, X. Li, L. Li, B. Li, D. Eremina, and H. Lu, An improved electronic colon cleansingmethod for detection of colonic polyps by virtual colonoscopy. IEEE Trans Biomed Eng,2006.53(8): p.1635-1646.
[67] I.W. Serlie, F.M. Vos, R. Truyen, F.H. Post, and L.J. van Vliet, Classifying CT image data into materialfractions by a scale and rotation invariant edge model. IEEE Trans Image Process,2007.16(12): p.2891-2904.
[68] M. Franaszek, R.M. Summers, P.J. Pickhardt, and J.R. Choi, Hybrid segmentation of colon filled with airand opacified fluid for CT colonography. IEEE Trans Med Imaging,2006.25(3): p.358-368.
[69] L. Ibanez and W. Schroeder, The ITK Software Guide.2003: Kitware.
[70] T.A. Chowdhury, P.F. Whelan, and O. Ghita, A fully automatic CAD-CTC system based on curvatureanalysis for standard and low-dose CT data. IEEE Trans Biomed Eng,2008.55(3): p.888-901.
[71] V. Caselles, R. Kimmel, and G. Sapiro, Geodesic active contours. International Journal of ComputerVision,1997.1(22): p.61-80.
[72] L. Lu, M. Wolf, J. Liang, M. Dundar, J. Bi, and M. Salganicoff, A two-level approach towards semanticcolon segmentation: removing extra-colonic findings. Med Image Comput Comput Assist Interv,2009.12(Pt2): p.1009-1016.
[73] L. Lu, An automatic colon cleansing method for virtual colonoscopy.2009First International Conferenceon Information Science and Engineering,2009p. icise, pp.1129-1132.
[74] https://imaging.nci.nih.gov/ncia.
[75] A.C. Silva, C.V. Wellnitz, and A.K. Hara, Three-dimensional virtual dissection at CT colonography:unraveling the colon to search for lesions. Radiographics,2006.26(6): p.1669-86.
[76] A.V. Bartroli, R. Wegenkittl, A. Konig, E. Groller, and E. Sorantin, Virtual colon flattening. DataVisualization2001,2001: p.127-364.
[77] W. Hong, X. Gu, F. Qiu, M. Jin, and A. kaufman, Conformal virtual colon flattening. Proceedings of the2006ACM symposium on Solid and physical modeling,2006: p.85-93.
[78] W. Hong, F. Qiu, and A. Kaufman, A pipeline for computer aided polyp detection. IEEE Trans VisComput Graph,2006.12(5): p.861-868.
[79] S. Haker, S. Angenent, A. Tannenbaum, and R. Kikinis, Nondistorting flattening maps and the3-Dvisualization of colon CT images. IEEE Trans Med Imaging,2000.19(7): p.665-670.
[80] W. Zeng, J. Marino, K. Chaitanya Gurijala, X. Gu, and A. Kaufman, Supine and prone colon registrationusing quasi-conformal mapping. IEEE Trans Vis Comput Graph,2010.16(6): p.1348-1357.
[81] S. Sudarsky, B. Geiger, C. Chefd'hotel, and L. Guendel, Colon unfolding via skeletal subspacedeformation. Med Image Comput Comput Assist Interv,2008.11(Pt2): p.205-212.
[82] J. Yao, A.S. Chowdhury, J. Aman, and R.M. Summers, Reversible projection technique for colonunfolding. IEEE Trans Biomed Eng,2010.57(12): p.2861-2869.
[83] D.S. Paik, C.F. Beaulieu, R.B. Jeffrey, Jr., C.A. Karadi, and S. Napel, Visualization modes for CTcolonography using cylindrical and planar map projections. J Comput Assist Tomogr,2000.24(2): p.179-188.
[84] K.T. Johnson, J.G. Fletcher, and C.D. Johnson, Computer-aided detection (CAD) using360degree virtualdissection: can CAD in a first reviewer paradigm be a reliable substitute for primary2D or3D search?Am J Roentgenol,2007.189(4): p.172-176.
[85] A.V. Bartroli, R. Wegenkittl, A. Konig, E. Groller, and E. Sorantin, Virtual colon flattening. DataVisualization2001,2001: p.127-140.
[86] A.C. Silva, C.V. Wellnitz, and A.K. Hara, Three-dimensional virtual dissection at CT colonography:unraveling the colon to search for lesions. Radiographics,2006.26(6): p.1669-1686.
[87] Z. Zhang, G. Wang, B.P. Brown, E.G. McFarland, J. Haller, and M.W. Vannier, Fast algorithm for softstraightening of the colon. Acad Radiol,2000.7(3): p.142-148.
[88] Z. Zhang, G. Wang, B.P. Brown, and M.W. Vannier, Distortion reduction for fast soft straightening of thecolon. Acad Radiol,2000.7(7): p.506-515.
[89] M.S. Hassouna, A.A. Farag, and R. Falk, Virtual fly-over: a new visualization technique for virtualcolonoscopy. Med Image Comput Comput Assist Interv,2006.9(Pt1): p.381-389.
[90] B.S. Shin, S. Lim, and H.J. Lee, Efficient unfolding of virtual endoscopy using linear ray interpolation.Comput Methods Programs Biomed,2009.93(2): p.174-184.
[91] D. Williams, S. Grimm, E. Coto, A. Roudsari, and H. Hatzakis, Volumetric Curved Planar Reformationfor virtual endoscopy. IEEE Trans Vis Comput Graph,2008.14(1): p.109-119.
[92] P. Carrascosa, C. Capunay, E.M. Lopez, M. Ulla, R. Castiglioni, and J. Carrascosa, Multidetector CTcolonoscopy: evaluation of the perspective-filet view virtual colon dissection technique for the detectionof elevated lesions. Abdom Imaging,2007.32(5): p.582-588.
[93] P. Carrascosa, E.M. Lopez, C. Capunay, J. Vallejos, and J. Carrascosa, Virtual colonoscopy in paediatricpatients Usefulness of a colon dissection technique. Eur J Radiol,2010.74(1): p.189-194.
[94] H. Hoppe, C. Quattropani, A. Spreng, J. Mattich, P. Netzer, and H.P. Dinkel, Virtual colon dissection withCT colonography compared with axial interpretation and conventional colonoscopy: preliminary results.AJR Am J Roentgenol,2004.182(5): p.1151-1158.
[95] S.H. Kim, J.M. Lee, H.W. Eun, M.W. Lee, J.K. Han, J.Y. Lee, and B.I. Choi, Two-versusthree-dimensional colon evaluation with recently developed virtual dissection software for CTcolonography. Radiology,2007.244(3): p.852-864.
[96] H. Ray, D. Silver, H. Pfister, and T. Cook, Ray casting architectures for volume visualization. IEEE TransVis Comput Graph,1999.5(3): p.210-223.
[97] J. Lewis, M. Cordner, and N. Fong. Pose Space Deformations: A Unified Approach to Shape Interpolationand Skeleton-Driven Deformation. Proceedings of ACM SIGGRAPH.2000.
[98] S. Haker, S. Angenent, A. Tannenbaum, R. Kikinis, G. Sapiro, and M. Halle, Conformal surfaceparameterization for texture mapping. IEEE Trans Vis Comput Graph,2000.6(2): p.181-189.
[99] F. Qiu, Z. Fan, X. Yin, A. kaufman, and X. Gu, Colon Flattening with Discrete Ricci Flow. MICCAIworkshop,2008: p.97-102.
[100] L. Lu and J. Zhao, An improved method of automatic colon segmentation for virtual colon unfolding.Comput Methods Programs Biomed,2013.109(1): p.1-12.
[101] V. Caselles, R. Kimmel, and G. Sapiro, Geodesic active contour. Int J Comput Vis,1997.22(1): p.61-79.
[102] D. Zhang, J. Zhao, and L. Lu, Virtual Eversion of Colon Based Outer-Surface Centerline, in YangtzeRiver2009International Congress on Medical Imaging Physics.2009: NanJing, China. p.194-201.
[103]陈维桓,微分几何.2006,北京:北京大学出版社.
[104] S. Sudarsky, B. Geiger, C. Chefd'hotel, and L. Guendel, Colon unfolding via skeletal subspacedeformation. Med Image Comput Comput Assist Interv,2008.11(Pt2): p.205-12.
[105] Z. Wang, Z. Liang, L. Li, J. Anderson, and D. Harringtion, Reduction of False Positives by InternalFeatures for Polyp Detection in CT-Based Virtual Colonoscopy. Med Phys.,2005.12(32): p.3602-3616.
[106] B.J. Qumseya and M.B. Wallace, Advanced colorectal polyp detection techniques. Curr GastroenterolRep,2012.14(5): p.414-420.
[107] S.Y. Park, D. Sargent, I. Spofford, K.G. Vosburgh, and A.R. Y, A colon video analysis framework forpolyp detection. IEEE Trans Biomed Eng,2012.59(5): p.1408-1418.
[108] J.G. Lee, J. Hyo Kim, S. Hyung Kim, H. Sun Park, and B. Ihn Choi, A straightforward approach tocomputer-aided polyp detection using a polyp-specific volumetric feature in CT colonography. ComputBiol Med,2011.41(9): p.790-801.
[109] P.N. Figueiredo, I.N. Figueiredo, S. Prasath, and R. Tsai, Automatic polyp detection in pillcam colon2capsule images and videos: preliminary feasibility report. Diagn Ther Endosc,2011.
[110] J.L.Ong and A.K.Seghouane, From Point to Local Neighborhood: Polyp Detection in CT ColonographyUsing Geodesic Ring Neighborhoods. IEEE Trans Image Process,2011.20(4): p.1000-1010.
[111] V.F.Ravesteijn, C.Wijk, F.Vos, R.Truyen, J.F.Peters, J.Stoker, and L. J.Vliet, Computer Aided Detection ofPolyps in CT Colonography Using Logistic Regression. IEEE Trans Image Process,2010.29(1): p.120-131.