医疗内窥镜视觉导航技术研究
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摘要
智能化医疗设备和医疗机器人技术研究，是一个多学科交叉的具有重要意义的研究领域。其研究和应用的一个重要方面是无创微创外科手术(MIS)，即利用人体的天生管腔或手术小孔来导入医疗器械或医疗机器人以实现对人体进行诊断、治疗、检测和手术等，从而减少手术期间对人体其他完好组织的伤害，缩短康复时间，并减轻患者的生理痛苦和医疗人员的手术操作时的心理压力。内窥镜诊疗术是微创外科的重要手段，其典型器材是内窥镜。肠道内窥镜是诊疗结肠癌等疾病的重要手段，但目前手工操作存在诸如穿孔等问题。因此，利用机器人和计算机技术对内窥镜诊疗设备进行智能化改造具有重要的研究意义和应用前景。
本论文以克服内窥镜检查穿孔、实现内窥镜智能化为目的，主要研究了智能内窥镜视觉导航技术，研究内容如下：
(1)本文针对内窥镜诊疗环境的特殊性和复杂性，通过调研，分析医生在内窥镜检查中的动作和决策方式，在此基础上提出了采用计算机视觉方法引导肠道内窥镜的介入的主要步骤：采集肠道内窥镜头部CCD观测的肠道实时图像并传输到计算机，计算机自动处理分析图像，自动控制和调节肠道内窥镜头部的姿态或给医生适当的建议使内窥镜顺利的进入肠道。
(2)图像底层处理算法是进行计算机视觉导航研究的基础，针对智能内窥镜视觉导航方案，本文从图像信息的采集开始，到图像信息的预处理、图像特征的提取等基本导航技术进行了概述和研究。
(3)在暗区提取方法方面：分析了暗区提取法的内窥镜导航原理，研究了简单阈值算法、基于最大类间方差法的自适应阈值分割算法和基于小波变换的阈值分割算法等三种暗区提取算法，并通过试验对三种算法进行了比较和分析。
(4)在纹理分析方法方面：分析了内窥镜图像暗区的形成过程以及利用暗区进行寻径的不稳定因素，根据肠道内存在闭合肌肉线的情况，研究了采用纹理分析法进行引导内窥镜头部的方法，并且给出了两种纹理分析算法——组织连接算法和边缘能量算法。通过试验，对两种算法进行对比分析。
(5)基于Dempster-Shafer证据推理法的传感器信息融合的导航策略：对暗区提取法和纹理分析法两种方法进行了具体的对比分析，并在此基础上提出了一种基于D-S证据推理法的能对两种导航方法进行信息融合的导航策略。经过试验证明，该导航策略能较好的对两种视觉导航方法进行信息融合。
(6)设计了一种新的智能内窥镜导航系统，该系统采用基于计算机视觉技术的主动避障、有力觉传感器的肠道内窥镜主动介入。
The research on intelligent medical devices and medical robots is currently an important area. Among its applications is the minimal invasive surgery (MIS), which has improved levels of traditional diagnosis and treatments. More and more forbidden zones of surgery could be reached and many kinds of diseases could be cured effectively. Endoscopy, an important technology of MIS, mainly uses endoscope as a diagnosis device. While colonoscopic diagnosis has become an effective therapy to cure colon illness, there exist some problems as perforation. Therefore, it is worthwhile to do research on intelligent modification for endoscopes.
This dissertation is mainly about the visual navigation technology of the endosope. The main contents of the dissertation are as follows:
(1) The particularity and complexity of the endoscopy diagnosis is introduced. By references and interviews with doctors, the manipulation strategy of doctors is analyzed and main steps for vision navigation in endoscopy diagnosis are proposed. The real-time images are picked up by CCD camera and sent to a computer. By analyzing these images, the computer automatically controls the pose of the tip of endoscope or gives suggestions to the doctor who pushes the endoscope into the colon successfully and safely.
(2) As a basis for detailed research on visual navigation, a series of techniques are investgated including endoscope images acquisition, pretreatment of endoscope images, feature extraction of image and so on. Several algorithms of these techniques are introduced as well.
(3) Dark region analysis: The principle of endoscope navigation based on dark region is introduced firstly. Three algorithms of auto-thresholding are presented which are used to find the path in the colon. These three auto-thresholding algorithms, known as the method of simple thresholding, the auto-thresholding algorithm based on Ostu's method and the histogram segmentation algorithm based on wavelet, are used to extract the lumen from colon images. The comparison among three algorithms is carried out.
(4) Contour analysis: At first, the limitation of dark region method is presented. According to the fact that there are many close muscle lines in colon surfaces, the method of contour analysis is introduced. Two algorithms, based on contour grouping and edge energe detecting respectively, are described to detecting path of the endoscope. The comparison between these algorithms is carried out.
(5) Navigation strategy: The application of multi-sensor navigation is introduced
本论文以克服内窥镜检查穿孔、实现内窥镜智能化为目的，主要研究了智能内窥镜视觉导航技术，研究内容如下：
(1)本文针对内窥镜诊疗环境的特殊性和复杂性，通过调研，分析医生在内窥镜检查中的动作和决策方式，在此基础上提出了采用计算机视觉方法引导肠道内窥镜的介入的主要步骤：采集肠道内窥镜头部CCD观测的肠道实时图像并传输到计算机，计算机自动处理分析图像，自动控制和调节肠道内窥镜头部的姿态或给医生适当的建议使内窥镜顺利的进入肠道。
(2)图像底层处理算法是进行计算机视觉导航研究的基础，针对智能内窥镜视觉导航方案，本文从图像信息的采集开始，到图像信息的预处理、图像特征的提取等基本导航技术进行了概述和研究。
(3)在暗区提取方法方面：分析了暗区提取法的内窥镜导航原理，研究了简单阈值算法、基于最大类间方差法的自适应阈值分割算法和基于小波变换的阈值分割算法等三种暗区提取算法，并通过试验对三种算法进行了比较和分析。
(4)在纹理分析方法方面：分析了内窥镜图像暗区的形成过程以及利用暗区进行寻径的不稳定因素，根据肠道内存在闭合肌肉线的情况，研究了采用纹理分析法进行引导内窥镜头部的方法，并且给出了两种纹理分析算法——组织连接算法和边缘能量算法。通过试验，对两种算法进行对比分析。
(5)基于Dempster-Shafer证据推理法的传感器信息融合的导航策略：对暗区提取法和纹理分析法两种方法进行了具体的对比分析，并在此基础上提出了一种基于D-S证据推理法的能对两种导航方法进行信息融合的导航策略。经过试验证明，该导航策略能较好的对两种视觉导航方法进行信息融合。
(6)设计了一种新的智能内窥镜导航系统，该系统采用基于计算机视觉技术的主动避障、有力觉传感器的肠道内窥镜主动介入。
The research on intelligent medical devices and medical robots is currently an important area. Among its applications is the minimal invasive surgery (MIS), which has improved levels of traditional diagnosis and treatments. More and more forbidden zones of surgery could be reached and many kinds of diseases could be cured effectively. Endoscopy, an important technology of MIS, mainly uses endoscope as a diagnosis device. While colonoscopic diagnosis has become an effective therapy to cure colon illness, there exist some problems as perforation. Therefore, it is worthwhile to do research on intelligent modification for endoscopes.
This dissertation is mainly about the visual navigation technology of the endosope. The main contents of the dissertation are as follows:
(1) The particularity and complexity of the endoscopy diagnosis is introduced. By references and interviews with doctors, the manipulation strategy of doctors is analyzed and main steps for vision navigation in endoscopy diagnosis are proposed. The real-time images are picked up by CCD camera and sent to a computer. By analyzing these images, the computer automatically controls the pose of the tip of endoscope or gives suggestions to the doctor who pushes the endoscope into the colon successfully and safely.
(2) As a basis for detailed research on visual navigation, a series of techniques are investgated including endoscope images acquisition, pretreatment of endoscope images, feature extraction of image and so on. Several algorithms of these techniques are introduced as well.
(3) Dark region analysis: The principle of endoscope navigation based on dark region is introduced firstly. Three algorithms of auto-thresholding are presented which are used to find the path in the colon. These three auto-thresholding algorithms, known as the method of simple thresholding, the auto-thresholding algorithm based on Ostu's method and the histogram segmentation algorithm based on wavelet, are used to extract the lumen from colon images. The comparison among three algorithms is carried out.
(4) Contour analysis: At first, the limitation of dark region method is presented. According to the fact that there are many close muscle lines in colon surfaces, the method of contour analysis is introduced. Two algorithms, based on contour grouping and edge energe detecting respectively, are described to detecting path of the endoscope. The comparison between these algorithms is carried out.
(5) Navigation strategy: The application of multi-sensor navigation is introduced
引文
[1] M. C. Carrozza, L. Lencioni, B. Magnani, A microrobot for colonoscopy, Proc. of the 7th International Symposium on Micro Machine and Human Science, pp. 223-228, 1996.
[2] R. C. H. Chiou, A. E. Kaufman, Z. R. Liang, et al. An Interactive Fly-Path Planning Using Potential Fields and Cell Decomposition for Virtual Endoscopy, IEEE Transaction on Nuclear Science, Vol. 46, No. 4, pp.1045-1049, Aug. 1999
[3] 孙振平，安向京，贺汉根，CITAVT-Ⅳ——觉导航的自主车，Vol．24，No．2，pp．115-121，2002．
[4] 石广田，俞焕然，李重庵等，工业机器人运动车体位姿计算方法研究，兰州大学学报(自然科学版)，Vol．34，No．2，pp．52-56，2001．
[5] 纪寿文，王荣本，徐友春等，智能车辆导航路径识别的模糊神经网络方法研究，中国图象图形学报，Vol．8(A)，No．2，pp．225-230，2003．
[6] 丑武胜，王天苗，医用机器人与数字化医疗仪器设备的研究和发展，机器人技术与应用，Vol．4，pp．7-11，2003．
[7] 人体解剖学编写组，人体解剖学，北京，高等教育出版社，1986．
[8] 郑思竟，人体解剖学，北京，人民卫生出版社，1986．
[9] 武汉医学院和上海第二医学院主编，外科学(上册)，北京，人民卫生出版社，1979．
[10] 郑芝田主编，胃肠病学，北京，人民卫生出版社，1986．
[11] 曾宪九译，克氏外科学(上册)，北京，人民卫生出版社，1983．
[12] 吴襄，生理学大纲(第五次修订)，北京，高等教育出版社，1987．
[13] 上海第一医学院医学卫生普及全书编辑委员会，医学卫生普及全书(外科)，上海，上海科学技术出版社，1960．
[14] 徐振耀，夏炜新，符影杰译，生物医学工程手册，天津，天津科技翻译出版公司，1993．
[15] 潘同宗，曹世植主编，现代胃肠病学，北京，科学出版社，1998．
[16] 萧树东主编，江绍基胃肠病学，上海，上海科学技术出版社，2001．
[17] 陈智，大肠肛管外科学，石家庄，河北科技出版社，1998．
[18] 大肠癌的诊治和预防，http://medical.ayinfo.ha.cn/ylchangshi/zhongliu10.htm, 2002.
[19] 张小勇，肖汉发，实用内镜检查与治疗学，湖南科学技术出版社，1997．
[20] K. Ikuta, M. Tsukamoto, S. Hirose, Shape memory alloy servo actuator system with electric resistance feedback and application for active endoscope, Proc. of IEEE Conference on Robotics and System, pp. 427-430, 1988.
[21] 高桥昌树，林俨，岩附信行，运动应用细管内移动研究，精密工学会誌，Vol．61(1)，pp．90-94，1995．
[22] 中国抗癌协会，新编常见恶性肿瘤诊治规范(大肠癌分册)，1999．
[23] 张达荣，夏维新，肠道疾病的诊断与防治，1994．
[24] W. B. Goddard, J. W. Bank, Robotic Endoscopy, U.S. Patent, No.5337732, Aug. 16, 1994.
[25] A. B. Skatlon and J. Burdick, The Development of Robotic Endoscope, Proceeding of IEEE International Conference on Intelligent Robots and Systems, pp. 162-171, 1995.
[26] 胡宗泰，医用内窥镜现状及发展趋势，世界医疗器械，Vol．3，No．1，pp．32-36，1997．
[27] 张世明，医用硬管内窥镜的发展，世界医疗器械，Vol．2，No．4，pp．32-35，1996．
[28] P. Dario, M. C. Carrozza, B. Magnani, et al, A Micro Robotic System for Colonoscopy, Proceeding of the 1997 IEEE International Conference on Robotics & Automation, pp.1567-1572, 1997.
[29] P. Dario, M. C. Carrozza, B. Allotta, et al, Micromechatronics in Medicine, IEEE/ASME Transactions on Mechatronics, Vol. 1, No.2, pp. 137-148, June 1996.
[30] M. C. Carrozza, L. Lencioni, S. D. Attanasio, et al, A sensorised robotic system for computer-asssisted colonoscopy, Proc. of the 7th International Symposium on Micro Machine and Human Science, pp. 26-33, 1996.
[31] M. C. Carrozza, L. Lencioni and B. Magnani, The development of a microrobot system for colonoscopy, Proc. of the 7th International Symposium on Micro Machine and Human Science, pp. 779-788, 1996.
[32] A. B. Slatkin, J. Burdick, W. Grundfest, The development of a robotic endoscope, Proc. of the 1995 IEEE International Conference on Intelligent Robotics and System, pp. 162-171, 1995.
[33] 颜国正，林良明，丁国清等，新型机器人驱动内窥镜系统的研究，高技术通讯，Vol．5，pp．61-62．2000．
[34] 高立明，林良明，颜国正，全方向蠕动机器人驱动内窥镜系统的研究，中国生物医学工程学报，Vol．17(1)，pp．36-41，1998．
[35] 林良明，颜国正，宋一然，微机械技术应用于医疗工程的研究，中国医疗器械杂志，Vol．23(5)，pp．258-264，1999．
[36] 米智楠，钱晋武，龚振邦等，内窥检查系统主动引导驱动技术的研究，高技术通讯，Vol．1，pp．70-81，2001．
[37] 李毅，柔性软管内移动机构及其驱动控制系统研究，硕士学位论文，上海大学，1999．
[38] 钱晋武，李毅，沈林勇，柔软管道中机器人蠕动机构研究，机械与电子，Vol．1，pp．37-38，2001．
[39] 米智楠，主动引导内窥检查机器人技术研究，博士学位论文，上海大学，2002．
[40] K. Ikeuchi, K. Yoshinaka, S. Hashimoto, et al, Locomotion of medical micro robot with spiral ribs using mucus, Proc. of 7th International Symposium on Micro Machine and Human Science, pp. 217-222, 1996
[41] R. H. Sturges, S. Laowattana, A Flexible Tendon-controlled Device for Endoscopy, The International Journal of Robotics Research, Vol. 12(2), pp. 121-131, 1993.
[42] S. Maeda, K. Abe, K. Yamamoto, et al, Active endoscope with SMA coil springs, Proc. of the IEEE Micro Electro Mechanical Systems (MEMS), pp. 290-295, 1996.
[43] S. Hirose, K. Ikuta and Y. Umetani, A New Design Method of Servo Actuators Based on The Shape Memory Effect, Proc. Of 5th RO. MAN. SY. Syrup. Udine, Italy, pp. 339-349, 1984.
[44] 杨杰，吴月华，张松，SMA大肠内窥镜的导向机理和控制计算，中国科技大学学报，Vol．28，No．1，1998．
[45] S. Dogramadzi, C. R. Allen and G. D. Bell, Computer controlled conlonoscopy, IEEE instrumentation and measurement technology conference, pp. 210-213, 1998.
[46] L. Dong, C. Xin, Z. Huiru, Research on determination of the 3D position of endoscope by magnetic field, Proceedings of SPIE-The International Society for Optical Engineering, Vol. 4077, pp. 343-346, 2000.
[47] 林东，陈新，三维空间磁场结构数学模型及磁场方式三维定位装置，福州大学学报(自然科学版)，Vol．31，No．2，pp．151-155，2003．
[48] 陈新，林东，张庆辉等，磁场方式的内窥镜体内三维定位与追踪方法研究，中国生物医学工程学报，Vol．21，No．5，pp．466-470，2002．
[49] 陈新，田村进一，林东等，磁传感方式的内窥镜三维定位与引导方法，计算机研究与发展，Vol．39，No．2，pp．242-246，2002．
[50] L. Zhang, J. Qian, L. Shen, et al, Novel FBG sensor devices for spatial shape detection of intelligent colonoscope, IEEE 2004 Conference on Robotics and Automation, ICRA2004, Vol. 1, pp. 834-840, 2004.
[51] L. Zhang, J. Qian, Y. Zhang, et al, On SDM/WDM FBG sensor net for shape detection of endoscope, IEEE 2005 Conference on Mechatronics and Automation, ICMA2005, 2005.
[52] 钱晋武，郑庆华，张伦伟等，渐进式内窥镜空间形状感知和重建，光学精密工程，Vol．12，No．5，pp．518-524，2004．
[53] Z. Liang, D. Chen, R. Chiou, et al, On segmentation of colon lumen for virtual colonoscopy, SPIE Medical Imaging, San Diego, to appear, 1999.
[54] H. Adachi, H. Takizawa, R. Ohta, et al, Development of a microfine active bending catheter equipped with MIF contact sensors, Proceedings of the sixth international micromachine symposium, pp. 193-198, November 9-10, 2000.
[55] 赵一珍，胶囊式视频内窥镜，世界医疗器械，Vol．9(1)，pp．47-49，2003．
[56] 行业信息，NORIKA胶囊式内窥镜，中国医疗器械信息，Vol．9，No．2，pp．35，2002．
[57] 孙萍，陈建宇，孙麒治，双层柔性铰链微小夹持器，上海大学学报，Vol．3(3)，pp．274-282，1997．
[58] 孙麒治，孙萍，秦新捷，细小管道内爬行的微机器人，光学精密工程，Vol．6(5)，pp．57-63，1998．
[59] 罗怡，孙麒治，惯性冲击型微机器人支撑腿受力及对运动速度影响分析，上海大学学报，Vol．6(2)，pp．100-102，2000．
[60] 卢普生，智能性凝胶在微机器人中的应用，中南工业大学学报，Vol．31，pp．423-425，2000
[61] D. A. Forsyth and J. Ponce, Computer Vision: A Modern Approach, Prentice Hall, 2003.
[62] 段峰，王耀南，雷晓峰等，机器视觉技术及其应用综述，自动化博览，Vol．3，pp．59-62，2002．
[63] 陈熙霖，视觉计算——人类感知能力的延伸，测控技术，Vol．19(5)，pp．7-12，2000．
[64] T. S. Newman, A. K. Jain, A survey of automated visual inspection, Computer Vision and Image Understanding, Vol. 61(2), pp. 231-262, 1995.
[65] 冯斌，汪懋华，基于颜色分形的水果计算机视觉分级技术，农业工程学报，Vol．18(2)，pp．141-143，2002．
[66] G. N. Khan and D. F. Gillies, Detecting insertion direction for an automatic endoscope, in Proc. IFIP 6th. World Congress on Medical Informatics, Singapore, December 1989, MEDINFO 89, pp. 455-459, North-Holland 1989.
[67] G. N. Khan and D. F. Gillies, A highly parallel shaded image segmentation method, in Parallel Processing for Computer Vision and Display, Eds. P. Dew, R. Earnshaw and T. Heywood, pp. 180-189, Addison Wesley England, 1989.
[68] K. V. Asari, S. Kumar and D. Radhakrishnan, Technique of distortion correction of endoscopic images by using a polynomial expansion, Med. Biol. Engrg. Computer, Vol. 37, pp. 8-12, 1999.
[69] S. Kumar, K. V. Asari and D. Radhakrishnan, Online extraction of lumen region and boundary from endoscopic images using a quad structure, in Proc. of IEEE Internat. Conf. on Image Processing and its Applications(IPA' 99), Manchester, UK, pp. 818-822, 1999.
[70] V. ASARI, S.KUMAR and I. KASSIM, A Fully Autonomous Microrobotic EndoscopySystem. Journal of Intelligent and Robotic Systems, Vol. 28, pp. 325-341, 2000.
[71] S. M. Krishnan, X. Yang and K. L. Chan, Image Processing for Planning the Navigational Path of a Microrobotic Endoscope, IFMBE Journal of Medical and Biological Engineering and Computing, Vol 37, Suppl 2, Part Ⅱ, pp 1108-1109, November 1999.
[72] K. C. Keong and D. F. Gillies, Using Fourier Information for the Detection of the Lumen in Endoscope images, IEEE Region 10's Ninth Annual International Conference, Proceeding of TENCON conference, Singapore, pp. 981-985, Aug. 1994.
[73] D. F. Gillies and G. N. Khan, Perceptual grouping and the Hough transform, in D. P. Casasent (ed.), Intelligent Robots and Computer Vision Ⅹ: Algorithms and Techniques, SPIE 1607, pp. 188-196, 1992.
[74] G. N. Khan and D. F. Gillies, A parallel-hierarchical method for grouping line segments into contours, SPIE's Proc. 33rd Int. Symposium, Application of Digital Image Processing Ⅻ, San Diego, CA, pp. 237-246, 1989.
[75] 朱宏擎，林良明，危剑辉，基于三次B样条小波的结肠镜图像暗区中心点估计的研究，中国医疗器械杂志，Vol．25，No．5，2001．
[76] H. Rashid, Shape from shading and motion parameter estimation under the near light source illumination, Ph D Thesis, Imperial College of Science, Technology and Medicine, London, 1991.
[77] L. E. Sucar, D. F. Gillies and H. Rashid, Integrating shape from shading in a gradient histogram and its application to endoscope navigation, 5th Int. Conf. on A. I. (ICAI-Ⅴ)Cancun, Mexico, 1992.
[78] T. Okatani and K. Deguchi, Shape Reconstruction from an Endoscope Image by Shape from Shading Technique for a Point Light Source at the Projection Center, Computer Vision and Image Understanding, Vol. 66, No. 2, May, pp. 119-131, 1997.
[79] Matrox Imaging, Matrox MeteorⅡ/Standard Installation and Hardware Refence, 2001.
[80] Matrox Imaging, Matrox imaging library help7, 1, 2002
[81] Matrox Imaging, Matrox imaging library user guide 7.0, 2002
[82] 叶晓东，朱兆达，中值滤波的快速算法，信号处理，Vol．13(3)，pp．227-230，1997．
[83] 沈庭芝，方子文，数字图象处理及模式识别，北京理工大学出版社，pp．34-47，1998．
[84] K．R．Castleman，数字图像处理，电子工业出版社，2002．
[85] M．Sonka，V．Hlavac，R．Boyle，图像处理、分析与机器视觉，人民邮电出版社，2003．
[86] D. F. Gillies and G. N. Khan, Endoscope insertion direction detecting method, U.S. Patent Numbers 4,910,590(March 20 1990) and 4,916,533(April 10 1990).
[87] D. F. Gillies, G. N. Khan and Y. Takahashi, Methods of detecting endoscope insertion direction, U.S. Patent Number 5,036,464(July 30 1991).
[88] M. Fleury, L. Hayat, A. F. Clark, Parallel entropic auto-thresholding, Image and Vision Computing, No. 14, pp. 247-263, 1996.
[89] 王茜蒨，彭中，刘莉，一种基于自适应阂值的图象分割算法，北京理工大学学报，Vol．23，No．4，pp．521-524，2003．
[90] G. Giralt, R. Sobek and R. Chatila, A multi-level planning and navigation system for a mobile robot: A first approach to HILARE, Proc. 6th Int. Joint Conf. Artificial Intelligence, Tokyo, Japan, pp. 335-337, 1979.
[91] R. Brooks, Solving the find-path problem by representing free space as generalized cylinders, MIT Artificial Intelligence Lab, Report, AI Memo No. 674, 1982
[92] S. Mallat, W. Hwang, Singularity detection and processing with wavelets, IEEE Transactions On IT, IT-38(2), pp. 617-643, 1992.
[93] 解梅，顾德仁，使用小波变换的图象边缘检测算法，电子科技大学学报，Vol．25(4)，pp． 353-356, 1996.
[94] S. Mallat, Multiresolution approximations and wavelet orthonormal bases of L~2(R). Trans. Amer. Amer. Math. Soc., Vol. 315, pp. 67-87, 1989.
[95] 刘建峰，陈丽亚，用小波变换进行图象的空域滤波．边缘检测与去噪，上海交通大学学报，Vol．29(6)，pp．132-136，1995．
[96] 王润生，图象理解，国防科技大学出版社，pp．88-96，1995．
[97] 崔屹，图像处理与分析——数学形态学方法及应用，科学出版社，2000．
[98] 戴青云，余英林，数学形态学在图像处理中的应用进展，控制理论与应用，Vol．18(4)，pp．478-481，2001．
[99] 车武军，杨勋年，汪国昭，动态骨架算法，软件学报，Vol．14，No．4，pp．818-823，2003．
[100] A. J. Descombes and T. Pun, Asynchronous perceptual grouping: from contours to relevant 2D structures, Computer vision and image understanding, Vol. 66, No. 1, pp. 1-24, 1997.
[101] W. Y. Ma and B. S. Manjunath, EdgeFlow: A Technique for Boundary Detection and Image Segmentation, IEEE Trans. Image Processing, Vol. 9, No. 8, pp. 1375-1388, Aug. 2000.
[102] 王宇生，一种基于积分变换的边缘检测方法，中国图形图像学报，Vol．7(A)，No．2，pp．145-149．2002．
[103] 王晓明，顾晓东，刘健，基于张量的图像边缘检测及滤波，中国图形图像学报，Vol．7(A)，No．8，pp．780-782，2002．
[104] L. G. Roberts, Machine Perception of Three-Dimension Solids, in Optical and Electro-Optimal Information Processing, J. T. Tippett, et al., Ed. Cambridge, MA: MIT Press, 99-159-197, 1965.
[105] J. Canny, A Computational Approach to Edge Detection, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. PAMI-8, No. 1, pp. 679-697, November 1986.
[106] W. T. Freeman, E. H. Adelson, The design and Use of Steerable Filters, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13, No. 9, pp. 891-906, September 1991.
[107] T. C. Folsom, R. B. Pinter, Primitive Features by Steering, Quadrature and Scale, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20 No. 11, pp.1161-1173, November 1998.
[108] W. T. Freeman, E. H. Edelson, Steerable filters for early vision, image analysis, and wavelet decomposition, Proc. 3rd Int. Conf. Comput. Vision (Osaka Japan), 1990
[109] 罗志增，蒋静坪，机器人感觉与多信息融合，机械工业出版社，2002
[110] 王长春，刘隆和，多传感器目标的模糊识别，雷达科学与技术，Vol．1，No．2，pp．69-73，2003
[111] 王光泰，周先敏，徐继麟，多传感器信息最优融合，电子科技大学学报，Vol．26，No．5，pp．465-467，1997．
[112] 张汝波，吴俊伟，顾国昌等，智能水下机器人多传感器信息融合的一种方法，哈尔滨工业大学学报，Vol．18，No．2，pp．72-76，1997．
[113] 廖熠，赵荣椿，从明暗恢复形状(SFS)的几类典型算法分析与评价，中国图象图形学报，Vol．6(A)，No．10，pp．953-961，2001．
[114] B. K. P. Horn, Obtaining shape from shading information, In the Psychology of Computer Vision. P. Winston(Ed.) McGraw-Hill, New York, 115-156, 1975
[115] B. K. P. Horn, Robot Vision, MIT Press, Cambridge, MA, 1986.
[116] B. K. P. Horn and R. W. Sjoberg, Calculating the reflectance map, Appl. Opt. 18(11), 1770-1779, 1979.
[117] R. Kimmel, K. Siddiqi, B. B. Kimia, et al, Shape from shading: Level set propagation and viscosity solutions, Int. J. Comput. Vision. Vol. 16, pp. 107-133, 1995.
[118] R. Kimmel and A. M. Bruckstein, Tracing level sets by level sets: A method for solving the shape from shading problem, Comput. Vision Image Understanding. Vol. 62(2), pp. 47-58, 1995.
[119] R. Kimmel and A. M. Bruckstein, Global shape from shading, Comput. Vision Image Understanding 62(3), pp. 360-369, 1995.
[120] A. M. Bruckstein, On shape from shading, Comput. Vision Graphics Image Process. Vol. 44, pp. 139-154, 1988.
[121] N. Oda, J. Hasegawa, T. Nonami, et al, Estimation of the surface topography from monocular endoscopic images, Opt. Commun. Vol. 109, pp. 215-221, 1994.
[122] J. Oliensis, Shape from shading as a partially well-constrained problem, Comput. Vision Graphics Image Process. Vol. 54, pp. 692-701, 1991.
[123] H. Rashid and P. Burger, Differential algorithm for the determination of shape from shading using a point light source, Image and Vision Computing. Vol. 10, No. 2, pp. 119-127, 1992.
[124] K. Deguchi, T. Sasano, H. Arai, et al, 3-D shape reconstruction from endoscope image sequences by the factorization method, Inst. Electron. Inf. Commun. Eng. Trans. IS, E79-D(9),, pp. 1329-1336, 1996.
[125] 殷金喜，基于触觉传感的智能内窥镜主动避障子系统研究，上海大学硕士学位论文，2004．
[126] 殷金喜，钱晋武，沈林勇等，利用硅微传感器实现智能内窥镜的主动避障，机电一体化，No．3，pp．21-24，2004．
[127] L. Shen, H. Que, J. Qian, et al, The Perforation-avoidance Endoscope System Based on Micro-Semiconductor Tactile Sensor. The First Asia International Symposium on Mechatronics(AISM 2004), pp. 819-824. September 27～30, 2004, Xi'an, China.
[128] L. Shen, J. Qian, Z. Zhang, et al, A micro-semiconductor tactile sensor for the obstacle-avoidance system of endoscope, Proceedings of the Sixth IEEE CPMT Conference on High Density Microsystem Design and Packaging and Component Failure Analysis, HDP'04, pp. 181-184, 2004.
[129] S. Boudjabil, A. Ferreiral, A. Krupa, Modeling and Vision-based Control of a Micro Catheter Head for Teleoperated In-Pipe Inspection, Proceedings of the 2003 IEEE, International Conference on Robotics & Automation, Taipei, Taiwan, September 14-19, 2003.
[130] 阙昊，机器人内窥镜智能辅助系统研究，上海大学硕士学位论文，2005．
[131] 阙昊，钱晋武，张震，基于肠道纹理轮廓的内窥镜视觉导向，中国图象图形学报，Vol．11，No．1，2006．
[132] 张宝军，机器人内窥镜主动避障子系统研究，上海大学硕士学位论文，2003．
[133] 罗继军，智能内窥镜辅助介入子系统研究，上海大学硕士学位论文，2003．
[134] 邓鹏，带力传感的内窥镜介入系统，上海大学硕士学位论文，2004．
[135] 罗继军，章亚男，沈林勇等，机器人主动内窥镜的自动介入技术初探，机电一体化，Vol．3，pp．21-23，2003．
[136] 邓鹏，章亚男，沈林勇等，一种力敏传感器在结肠镜介入力监控中的应用，上海大学学报，Vol．11，No．1，pp．32-36，2005．
[137] 张宝军，沈林勇，钱晋武，串行通讯在机器人内窥镜主动避障监控系统中的应用，上海大学学报(自然科学版)，Vol．9，No．2，pp．113-117，2003．
[138] 阙昊，张宝军，钱晋武，内窥镜前端避障中的手柄自动控制装置，机电一体化，Vol．10， No．1，pp．32-33，2004。
[139] 冯亮，阙吴，钱晋武等，智能内窥机器人系统远程诊疗初探，光学精密工程，Vol．12，No．3，pp．11-16，2004．
[140] 秦新捷，章亚男，张祖仁等，全自动智能内窥镜系统试验平台的研究与设计，光学精密工程，Vol．12，No．3，pp．288-291，2004．
[141] 钱晋武，张震，章亚男等，智能内窥镜视觉导航技术和系统研究，光学精密工程，Vol．12，No．3，pp．76-80，2004．
[2] R. C. H. Chiou, A. E. Kaufman, Z. R. Liang, et al. An Interactive Fly-Path Planning Using Potential Fields and Cell Decomposition for Virtual Endoscopy, IEEE Transaction on Nuclear Science, Vol. 46, No. 4, pp.1045-1049, Aug. 1999
[3] 孙振平，安向京，贺汉根，CITAVT-Ⅳ——觉导航的自主车，Vol．24，No．2，pp．115-121，2002．
[4] 石广田，俞焕然，李重庵等，工业机器人运动车体位姿计算方法研究，兰州大学学报(自然科学版)，Vol．34，No．2，pp．52-56，2001．
[5] 纪寿文，王荣本，徐友春等，智能车辆导航路径识别的模糊神经网络方法研究，中国图象图形学报，Vol．8(A)，No．2，pp．225-230，2003．
[6] 丑武胜，王天苗，医用机器人与数字化医疗仪器设备的研究和发展，机器人技术与应用，Vol．4，pp．7-11，2003．
[7] 人体解剖学编写组，人体解剖学，北京，高等教育出版社，1986．
[8] 郑思竟，人体解剖学，北京，人民卫生出版社，1986．
[9] 武汉医学院和上海第二医学院主编，外科学(上册)，北京，人民卫生出版社，1979．
[10] 郑芝田主编，胃肠病学，北京，人民卫生出版社，1986．
[11] 曾宪九译，克氏外科学(上册)，北京，人民卫生出版社，1983．
[12] 吴襄，生理学大纲(第五次修订)，北京，高等教育出版社，1987．
[13] 上海第一医学院医学卫生普及全书编辑委员会，医学卫生普及全书(外科)，上海，上海科学技术出版社，1960．
[14] 徐振耀，夏炜新，符影杰译，生物医学工程手册，天津，天津科技翻译出版公司，1993．
[15] 潘同宗，曹世植主编，现代胃肠病学，北京，科学出版社，1998．
[16] 萧树东主编，江绍基胃肠病学，上海，上海科学技术出版社，2001．
[17] 陈智，大肠肛管外科学，石家庄，河北科技出版社，1998．
[18] 大肠癌的诊治和预防，http://medical.ayinfo.ha.cn/ylchangshi/zhongliu10.htm, 2002.
[19] 张小勇，肖汉发，实用内镜检查与治疗学，湖南科学技术出版社，1997．
[20] K. Ikuta, M. Tsukamoto, S. Hirose, Shape memory alloy servo actuator system with electric resistance feedback and application for active endoscope, Proc. of IEEE Conference on Robotics and System, pp. 427-430, 1988.
[21] 高桥昌树，林俨，岩附信行，运动应用细管内移动研究，精密工学会誌，Vol．61(1)，pp．90-94，1995．
[22] 中国抗癌协会，新编常见恶性肿瘤诊治规范(大肠癌分册)，1999．
[23] 张达荣，夏维新，肠道疾病的诊断与防治，1994．
[24] W. B. Goddard, J. W. Bank, Robotic Endoscopy, U.S. Patent, No.5337732, Aug. 16, 1994.
[25] A. B. Skatlon and J. Burdick, The Development of Robotic Endoscope, Proceeding of IEEE International Conference on Intelligent Robots and Systems, pp. 162-171, 1995.
[26] 胡宗泰，医用内窥镜现状及发展趋势，世界医疗器械，Vol．3，No．1，pp．32-36，1997．
[27] 张世明，医用硬管内窥镜的发展，世界医疗器械，Vol．2，No．4，pp．32-35，1996．
[28] P. Dario, M. C. Carrozza, B. Magnani, et al, A Micro Robotic System for Colonoscopy, Proceeding of the 1997 IEEE International Conference on Robotics & Automation, pp.1567-1572, 1997.
[29] P. Dario, M. C. Carrozza, B. Allotta, et al, Micromechatronics in Medicine, IEEE/ASME Transactions on Mechatronics, Vol. 1, No.2, pp. 137-148, June 1996.
[30] M. C. Carrozza, L. Lencioni, S. D. Attanasio, et al, A sensorised robotic system for computer-asssisted colonoscopy, Proc. of the 7th International Symposium on Micro Machine and Human Science, pp. 26-33, 1996.
[31] M. C. Carrozza, L. Lencioni and B. Magnani, The development of a microrobot system for colonoscopy, Proc. of the 7th International Symposium on Micro Machine and Human Science, pp. 779-788, 1996.
[32] A. B. Slatkin, J. Burdick, W. Grundfest, The development of a robotic endoscope, Proc. of the 1995 IEEE International Conference on Intelligent Robotics and System, pp. 162-171, 1995.
[33] 颜国正，林良明，丁国清等，新型机器人驱动内窥镜系统的研究，高技术通讯，Vol．5，pp．61-62．2000．
[34] 高立明，林良明，颜国正，全方向蠕动机器人驱动内窥镜系统的研究，中国生物医学工程学报，Vol．17(1)，pp．36-41，1998．
[35] 林良明，颜国正，宋一然，微机械技术应用于医疗工程的研究，中国医疗器械杂志，Vol．23(5)，pp．258-264，1999．
[36] 米智楠，钱晋武，龚振邦等，内窥检查系统主动引导驱动技术的研究，高技术通讯，Vol．1，pp．70-81，2001．
[37] 李毅，柔性软管内移动机构及其驱动控制系统研究，硕士学位论文，上海大学，1999．
[38] 钱晋武，李毅，沈林勇，柔软管道中机器人蠕动机构研究，机械与电子，Vol．1，pp．37-38，2001．
[39] 米智楠，主动引导内窥检查机器人技术研究，博士学位论文，上海大学，2002．
[40] K. Ikeuchi, K. Yoshinaka, S. Hashimoto, et al, Locomotion of medical micro robot with spiral ribs using mucus, Proc. of 7th International Symposium on Micro Machine and Human Science, pp. 217-222, 1996
[41] R. H. Sturges, S. Laowattana, A Flexible Tendon-controlled Device for Endoscopy, The International Journal of Robotics Research, Vol. 12(2), pp. 121-131, 1993.
[42] S. Maeda, K. Abe, K. Yamamoto, et al, Active endoscope with SMA coil springs, Proc. of the IEEE Micro Electro Mechanical Systems (MEMS), pp. 290-295, 1996.
[43] S. Hirose, K. Ikuta and Y. Umetani, A New Design Method of Servo Actuators Based on The Shape Memory Effect, Proc. Of 5th RO. MAN. SY. Syrup. Udine, Italy, pp. 339-349, 1984.
[44] 杨杰，吴月华，张松，SMA大肠内窥镜的导向机理和控制计算，中国科技大学学报，Vol．28，No．1，1998．
[45] S. Dogramadzi, C. R. Allen and G. D. Bell, Computer controlled conlonoscopy, IEEE instrumentation and measurement technology conference, pp. 210-213, 1998.
[46] L. Dong, C. Xin, Z. Huiru, Research on determination of the 3D position of endoscope by magnetic field, Proceedings of SPIE-The International Society for Optical Engineering, Vol. 4077, pp. 343-346, 2000.
[47] 林东，陈新，三维空间磁场结构数学模型及磁场方式三维定位装置，福州大学学报(自然科学版)，Vol．31，No．2，pp．151-155，2003．
[48] 陈新，林东，张庆辉等，磁场方式的内窥镜体内三维定位与追踪方法研究，中国生物医学工程学报，Vol．21，No．5，pp．466-470，2002．
[49] 陈新，田村进一，林东等，磁传感方式的内窥镜三维定位与引导方法，计算机研究与发展，Vol．39，No．2，pp．242-246，2002．
[50] L. Zhang, J. Qian, L. Shen, et al, Novel FBG sensor devices for spatial shape detection of intelligent colonoscope, IEEE 2004 Conference on Robotics and Automation, ICRA2004, Vol. 1, pp. 834-840, 2004.
[51] L. Zhang, J. Qian, Y. Zhang, et al, On SDM/WDM FBG sensor net for shape detection of endoscope, IEEE 2005 Conference on Mechatronics and Automation, ICMA2005, 2005.
[52] 钱晋武，郑庆华，张伦伟等，渐进式内窥镜空间形状感知和重建，光学精密工程，Vol．12，No．5，pp．518-524，2004．
[53] Z. Liang, D. Chen, R. Chiou, et al, On segmentation of colon lumen for virtual colonoscopy, SPIE Medical Imaging, San Diego, to appear, 1999.
[54] H. Adachi, H. Takizawa, R. Ohta, et al, Development of a microfine active bending catheter equipped with MIF contact sensors, Proceedings of the sixth international micromachine symposium, pp. 193-198, November 9-10, 2000.
[55] 赵一珍，胶囊式视频内窥镜，世界医疗器械，Vol．9(1)，pp．47-49，2003．
[56] 行业信息，NORIKA胶囊式内窥镜，中国医疗器械信息，Vol．9，No．2，pp．35，2002．
[57] 孙萍，陈建宇，孙麒治，双层柔性铰链微小夹持器，上海大学学报，Vol．3(3)，pp．274-282，1997．
[58] 孙麒治，孙萍，秦新捷，细小管道内爬行的微机器人，光学精密工程，Vol．6(5)，pp．57-63，1998．
[59] 罗怡，孙麒治，惯性冲击型微机器人支撑腿受力及对运动速度影响分析，上海大学学报，Vol．6(2)，pp．100-102，2000．
[60] 卢普生，智能性凝胶在微机器人中的应用，中南工业大学学报，Vol．31，pp．423-425，2000
[61] D. A. Forsyth and J. Ponce, Computer Vision: A Modern Approach, Prentice Hall, 2003.
[62] 段峰，王耀南，雷晓峰等，机器视觉技术及其应用综述，自动化博览，Vol．3，pp．59-62，2002．
[63] 陈熙霖，视觉计算——人类感知能力的延伸，测控技术，Vol．19(5)，pp．7-12，2000．
[64] T. S. Newman, A. K. Jain, A survey of automated visual inspection, Computer Vision and Image Understanding, Vol. 61(2), pp. 231-262, 1995.
[65] 冯斌，汪懋华，基于颜色分形的水果计算机视觉分级技术，农业工程学报，Vol．18(2)，pp．141-143，2002．
[66] G. N. Khan and D. F. Gillies, Detecting insertion direction for an automatic endoscope, in Proc. IFIP 6th. World Congress on Medical Informatics, Singapore, December 1989, MEDINFO 89, pp. 455-459, North-Holland 1989.
[67] G. N. Khan and D. F. Gillies, A highly parallel shaded image segmentation method, in Parallel Processing for Computer Vision and Display, Eds. P. Dew, R. Earnshaw and T. Heywood, pp. 180-189, Addison Wesley England, 1989.
[68] K. V. Asari, S. Kumar and D. Radhakrishnan, Technique of distortion correction of endoscopic images by using a polynomial expansion, Med. Biol. Engrg. Computer, Vol. 37, pp. 8-12, 1999.
[69] S. Kumar, K. V. Asari and D. Radhakrishnan, Online extraction of lumen region and boundary from endoscopic images using a quad structure, in Proc. of IEEE Internat. Conf. on Image Processing and its Applications(IPA' 99), Manchester, UK, pp. 818-822, 1999.
[70] V. ASARI, S.KUMAR and I. KASSIM, A Fully Autonomous Microrobotic EndoscopySystem. Journal of Intelligent and Robotic Systems, Vol. 28, pp. 325-341, 2000.
[71] S. M. Krishnan, X. Yang and K. L. Chan, Image Processing for Planning the Navigational Path of a Microrobotic Endoscope, IFMBE Journal of Medical and Biological Engineering and Computing, Vol 37, Suppl 2, Part Ⅱ, pp 1108-1109, November 1999.
[72] K. C. Keong and D. F. Gillies, Using Fourier Information for the Detection of the Lumen in Endoscope images, IEEE Region 10's Ninth Annual International Conference, Proceeding of TENCON conference, Singapore, pp. 981-985, Aug. 1994.
[73] D. F. Gillies and G. N. Khan, Perceptual grouping and the Hough transform, in D. P. Casasent (ed.), Intelligent Robots and Computer Vision Ⅹ: Algorithms and Techniques, SPIE 1607, pp. 188-196, 1992.
[74] G. N. Khan and D. F. Gillies, A parallel-hierarchical method for grouping line segments into contours, SPIE's Proc. 33rd Int. Symposium, Application of Digital Image Processing Ⅻ, San Diego, CA, pp. 237-246, 1989.
[75] 朱宏擎，林良明，危剑辉，基于三次B样条小波的结肠镜图像暗区中心点估计的研究，中国医疗器械杂志，Vol．25，No．5，2001．
[76] H. Rashid, Shape from shading and motion parameter estimation under the near light source illumination, Ph D Thesis, Imperial College of Science, Technology and Medicine, London, 1991.
[77] L. E. Sucar, D. F. Gillies and H. Rashid, Integrating shape from shading in a gradient histogram and its application to endoscope navigation, 5th Int. Conf. on A. I. (ICAI-Ⅴ)Cancun, Mexico, 1992.
[78] T. Okatani and K. Deguchi, Shape Reconstruction from an Endoscope Image by Shape from Shading Technique for a Point Light Source at the Projection Center, Computer Vision and Image Understanding, Vol. 66, No. 2, May, pp. 119-131, 1997.
[79] Matrox Imaging, Matrox MeteorⅡ/Standard Installation and Hardware Refence, 2001.
[80] Matrox Imaging, Matrox imaging library help7, 1, 2002
[81] Matrox Imaging, Matrox imaging library user guide 7.0, 2002
[82] 叶晓东，朱兆达，中值滤波的快速算法，信号处理，Vol．13(3)，pp．227-230，1997．
[83] 沈庭芝，方子文，数字图象处理及模式识别，北京理工大学出版社，pp．34-47，1998．
[84] K．R．Castleman，数字图像处理，电子工业出版社，2002．
[85] M．Sonka，V．Hlavac，R．Boyle，图像处理、分析与机器视觉，人民邮电出版社，2003．
[86] D. F. Gillies and G. N. Khan, Endoscope insertion direction detecting method, U.S. Patent Numbers 4,910,590(March 20 1990) and 4,916,533(April 10 1990).
[87] D. F. Gillies, G. N. Khan and Y. Takahashi, Methods of detecting endoscope insertion direction, U.S. Patent Number 5,036,464(July 30 1991).
[88] M. Fleury, L. Hayat, A. F. Clark, Parallel entropic auto-thresholding, Image and Vision Computing, No. 14, pp. 247-263, 1996.
[89] 王茜蒨，彭中，刘莉，一种基于自适应阂值的图象分割算法，北京理工大学学报，Vol．23，No．4，pp．521-524，2003．
[90] G. Giralt, R. Sobek and R. Chatila, A multi-level planning and navigation system for a mobile robot: A first approach to HILARE, Proc. 6th Int. Joint Conf. Artificial Intelligence, Tokyo, Japan, pp. 335-337, 1979.
[91] R. Brooks, Solving the find-path problem by representing free space as generalized cylinders, MIT Artificial Intelligence Lab, Report, AI Memo No. 674, 1982
[92] S. Mallat, W. Hwang, Singularity detection and processing with wavelets, IEEE Transactions On IT, IT-38(2), pp. 617-643, 1992.
[93] 解梅，顾德仁，使用小波变换的图象边缘检测算法，电子科技大学学报，Vol．25(4)，pp． 353-356, 1996.
[94] S. Mallat, Multiresolution approximations and wavelet orthonormal bases of L~2(R). Trans. Amer. Amer. Math. Soc., Vol. 315, pp. 67-87, 1989.
[95] 刘建峰，陈丽亚，用小波变换进行图象的空域滤波．边缘检测与去噪，上海交通大学学报，Vol．29(6)，pp．132-136，1995．
[96] 王润生，图象理解，国防科技大学出版社，pp．88-96，1995．
[97] 崔屹，图像处理与分析——数学形态学方法及应用，科学出版社，2000．
[98] 戴青云，余英林，数学形态学在图像处理中的应用进展，控制理论与应用，Vol．18(4)，pp．478-481，2001．
[99] 车武军，杨勋年，汪国昭，动态骨架算法，软件学报，Vol．14，No．4，pp．818-823，2003．
[100] A. J. Descombes and T. Pun, Asynchronous perceptual grouping: from contours to relevant 2D structures, Computer vision and image understanding, Vol. 66, No. 1, pp. 1-24, 1997.
[101] W. Y. Ma and B. S. Manjunath, EdgeFlow: A Technique for Boundary Detection and Image Segmentation, IEEE Trans. Image Processing, Vol. 9, No. 8, pp. 1375-1388, Aug. 2000.
[102] 王宇生，一种基于积分变换的边缘检测方法，中国图形图像学报，Vol．7(A)，No．2，pp．145-149．2002．
[103] 王晓明，顾晓东，刘健，基于张量的图像边缘检测及滤波，中国图形图像学报，Vol．7(A)，No．8，pp．780-782，2002．
[104] L. G. Roberts, Machine Perception of Three-Dimension Solids, in Optical and Electro-Optimal Information Processing, J. T. Tippett, et al., Ed. Cambridge, MA: MIT Press, 99-159-197, 1965.
[105] J. Canny, A Computational Approach to Edge Detection, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. PAMI-8, No. 1, pp. 679-697, November 1986.
[106] W. T. Freeman, E. H. Adelson, The design and Use of Steerable Filters, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13, No. 9, pp. 891-906, September 1991.
[107] T. C. Folsom, R. B. Pinter, Primitive Features by Steering, Quadrature and Scale, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20 No. 11, pp.1161-1173, November 1998.
[108] W. T. Freeman, E. H. Edelson, Steerable filters for early vision, image analysis, and wavelet decomposition, Proc. 3rd Int. Conf. Comput. Vision (Osaka Japan), 1990
[109] 罗志增，蒋静坪，机器人感觉与多信息融合，机械工业出版社，2002
[110] 王长春，刘隆和，多传感器目标的模糊识别，雷达科学与技术，Vol．1，No．2，pp．69-73，2003
[111] 王光泰，周先敏，徐继麟，多传感器信息最优融合，电子科技大学学报，Vol．26，No．5，pp．465-467，1997．
[112] 张汝波，吴俊伟，顾国昌等，智能水下机器人多传感器信息融合的一种方法，哈尔滨工业大学学报，Vol．18，No．2，pp．72-76，1997．
[113] 廖熠，赵荣椿，从明暗恢复形状(SFS)的几类典型算法分析与评价，中国图象图形学报，Vol．6(A)，No．10，pp．953-961，2001．
[114] B. K. P. Horn, Obtaining shape from shading information, In the Psychology of Computer Vision. P. Winston(Ed.) McGraw-Hill, New York, 115-156, 1975
[115] B. K. P. Horn, Robot Vision, MIT Press, Cambridge, MA, 1986.
[116] B. K. P. Horn and R. W. Sjoberg, Calculating the reflectance map, Appl. Opt. 18(11), 1770-1779, 1979.
[117] R. Kimmel, K. Siddiqi, B. B. Kimia, et al, Shape from shading: Level set propagation and viscosity solutions, Int. J. Comput. Vision. Vol. 16, pp. 107-133, 1995.
[118] R. Kimmel and A. M. Bruckstein, Tracing level sets by level sets: A method for solving the shape from shading problem, Comput. Vision Image Understanding. Vol. 62(2), pp. 47-58, 1995.
[119] R. Kimmel and A. M. Bruckstein, Global shape from shading, Comput. Vision Image Understanding 62(3), pp. 360-369, 1995.
[120] A. M. Bruckstein, On shape from shading, Comput. Vision Graphics Image Process. Vol. 44, pp. 139-154, 1988.
[121] N. Oda, J. Hasegawa, T. Nonami, et al, Estimation of the surface topography from monocular endoscopic images, Opt. Commun. Vol. 109, pp. 215-221, 1994.
[122] J. Oliensis, Shape from shading as a partially well-constrained problem, Comput. Vision Graphics Image Process. Vol. 54, pp. 692-701, 1991.
[123] H. Rashid and P. Burger, Differential algorithm for the determination of shape from shading using a point light source, Image and Vision Computing. Vol. 10, No. 2, pp. 119-127, 1992.
[124] K. Deguchi, T. Sasano, H. Arai, et al, 3-D shape reconstruction from endoscope image sequences by the factorization method, Inst. Electron. Inf. Commun. Eng. Trans. IS, E79-D(9),, pp. 1329-1336, 1996.
[125] 殷金喜，基于触觉传感的智能内窥镜主动避障子系统研究，上海大学硕士学位论文，2004．
[126] 殷金喜，钱晋武，沈林勇等，利用硅微传感器实现智能内窥镜的主动避障，机电一体化，No．3，pp．21-24，2004．
[127] L. Shen, H. Que, J. Qian, et al, The Perforation-avoidance Endoscope System Based on Micro-Semiconductor Tactile Sensor. The First Asia International Symposium on Mechatronics(AISM 2004), pp. 819-824. September 27～30, 2004, Xi'an, China.
[128] L. Shen, J. Qian, Z. Zhang, et al, A micro-semiconductor tactile sensor for the obstacle-avoidance system of endoscope, Proceedings of the Sixth IEEE CPMT Conference on High Density Microsystem Design and Packaging and Component Failure Analysis, HDP'04, pp. 181-184, 2004.
[129] S. Boudjabil, A. Ferreiral, A. Krupa, Modeling and Vision-based Control of a Micro Catheter Head for Teleoperated In-Pipe Inspection, Proceedings of the 2003 IEEE, International Conference on Robotics & Automation, Taipei, Taiwan, September 14-19, 2003.
[130] 阙昊，机器人内窥镜智能辅助系统研究，上海大学硕士学位论文，2005．
[131] 阙昊，钱晋武，张震，基于肠道纹理轮廓的内窥镜视觉导向，中国图象图形学报，Vol．11，No．1，2006．
[132] 张宝军，机器人内窥镜主动避障子系统研究，上海大学硕士学位论文，2003．
[133] 罗继军，智能内窥镜辅助介入子系统研究，上海大学硕士学位论文，2003．
[134] 邓鹏，带力传感的内窥镜介入系统，上海大学硕士学位论文，2004．
[135] 罗继军，章亚男，沈林勇等，机器人主动内窥镜的自动介入技术初探，机电一体化，Vol．3，pp．21-23，2003．
[136] 邓鹏，章亚男，沈林勇等，一种力敏传感器在结肠镜介入力监控中的应用，上海大学学报，Vol．11，No．1，pp．32-36，2005．
[137] 张宝军，沈林勇，钱晋武，串行通讯在机器人内窥镜主动避障监控系统中的应用，上海大学学报(自然科学版)，Vol．9，No．2，pp．113-117，2003．
[138] 阙昊，张宝军，钱晋武，内窥镜前端避障中的手柄自动控制装置，机电一体化，Vol．10， No．1，pp．32-33，2004。
[139] 冯亮，阙吴，钱晋武等，智能内窥机器人系统远程诊疗初探，光学精密工程，Vol．12，No．3，pp．11-16，2004．
[140] 秦新捷，章亚男，张祖仁等，全自动智能内窥镜系统试验平台的研究与设计，光学精密工程，Vol．12，No．3，pp．288-291，2004．
[141] 钱晋武，张震，章亚男等，智能内窥镜视觉导航技术和系统研究，光学精密工程，Vol．12，No．3，pp．76-80，2004．