Freehand三维超声体数据重建的最新研究进展

doi:10.3969/j.issn.0258-8021. 2017. 01.012

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (2824 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Freehand 3D ultrasound imaging system is more in line with doctor's habits and the surrounding of operating room for its simple, useful, wider field of view and higher image resolution, which makes it one of the research focuses in the field of guidance of interventional surgery based on ultrasound imaging. Freehand 3D ultrasound produces 3D volume data of anatomical objects from a sequence of irregularly located 2D B-mode ultrasound images, and renders the reconstructed 3D volume data. Volume reconstruction is one of the key procedures in freehand 3D ultrasound imaging system and plays an important role in improving the reconstructed image quality. This paper summed up three kinds of volume reconstruction methods for freehand 3D ultrasound image, incuding voxel-based method, pixel-based method and function-based method. After that, some algorithms are presented with their merits and drawbacks. Finally, the research progress is summarized and future research directions are suggested.

Key words： freehand 3D ultrasound volume data reconstruction reconstruction algorithms

Received: 10 May 2016

PACS:

R318

About author:: (Senior member, Chinese Society of Biomedical Engineering)

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Fan Yangyang
	Ni Qian
	Wen Tiexiang
	Gu Jia
	Wang Lei
	Xie Yaoqin
	Liu Jingen

Cite this article:

Fan Yangyang,Ni Qian,Wen Tiexiang, et al. The Latest Research Progress of Freehand 3D US Volume Reconstruction[J]. Chinese Journal of Biomedical Engineering, 2017, 36(1): 92-102.

URL:

http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021. 2017. 01.012 OR http://cjbme.csbme.org/EN/Y2017/V36/I1/92

[1] 胡伟.自由臂超声三维图像快速重建算法研究 [D]. 广州:华南理工大学, 2013.
[2] Varandas J, Baptista P, Santos J, et al. VOLUS-a visualization system for 3D ultrasound data [J]. Ultrasonics, 2004, 42(1): 689-694.
[3] Inglis S, Derek C, John PL. A novel three-dimensional endoscopic ultrasound technique for the freehand examination of the oesophagus [J]. Ultrasound in Medicine & Biology, 2011, 37(11): 1779-1790.
[4] 田增民,孙君昭,杜吉祥,等. 3D超声导航系统在神经外科手术中的应用 [J]. 第二军区大学报, 2015, 26(12): 1384-1387.
[5] 徐静,杨向东,朱森强,等. 用于肝癌介入治疗的术中三维超声导航系统 [J]. 中国生物医学工程学报, 2007, 26(5): 719-723.
[6] 孙银山. 基于三维超声图像的穿刺手术机器人辅助系统研究 [D]. 哈尔滨:哈尔滨工业大学, 2011.
[7] 何宇. 经阴道三维超声在妇科疾病诊断中的应用 [D]. 吉林:吉林大学, 2013.
[8] Jiang Weiwei, Li Anhua, Zheng Yongping. A semi-automated 3D annotation method for breast ultrasound imaging: system development and feasibility study on phantoms [J]. Ultrasound in Medicine & Biology, 2014, 40(2): 434-446.
[9] 李曦,陈光杰. 三维超声成像原理及其发展 [J]. 中国医学物理学杂志,2001,18(3):136-140.
[10] Fenster A, Bax J, Neshat H, et al. Advancements and breakthroughs in ultrasound imaging: 3D ultrasound imaging in image-guided intervention [M].Rijeka: InTech Open Access Publisher, 2013.
[11] Mercier L, Petrecca K, Araujo D, et al. Online database of brain tumor images [EB/OL]. http://dx.doi.org/10.1118/1.4709600/ 2012- 05-22/2016-05-11.
[12] Huang Qinghua, Zheng Yongping. An adaptive squared-distance weighted interpolation for volume reconstruction in 3D freehand ultrasound [J]. Ultrasonics, 2006, 44(1): 73-77.
[13] 郭强,许健,杨新,等. 基于MAP-MRF的旋转3维超声心动图断层重建及降噪 [J]. 中国图象图形学报, 2005, 10(10): 1281-1288.
[14] Huang Qinghua, Huang Yanping, Hu Wei, et al. Bezier interpolation for 3D freehand ultrasound [J]. IEEE Transactions on Human-Machine Systems, 2015, 45(3): 385-392.
[15] Kuhl CK, Schrading S, Leutner CC, et al. Mammography, breast ultrasound, and magnetic resonance imaging for surveillance of women at high familial risk for breast cancer [J]. Journal of Clinical Oncology, 2005, 23(33): 8469-8476.
[16] Warner E, Plewes DB, Shumak RS, et al. Comparison of breast magnetic resonance imaging, mammography, and ultrasound for surveillance of women at high risk for hereditary breast cancer [J]. Journal of Clinical Oncology, 2001, 19(15): 3524-3531.
[17] Duric N, Littrup P, Li C, et al. Breast ultrasound tomography: bridging the gap to clinical practice [C] //Bosch JG. Medical Imaging 2012: Ultrasonic Imaging, Tomography, and Therapy. San Diego: SPIE, 2012, 8320: 83200O1-83200O9.
[18] Delphinus medical technologies [EB/OL]. http://www.delphinusmt. com/2014-09-19/2016-07-20.
[19] 温铁祥. 自由式三维医学超声重建关键技术研究 [D]. 深圳:中国科学院大学, 2014.
[20] Gee AH, Prager RW, Treece GM, et al. Engineering a freehand 3D ultrasound system [J]. Pattern Recognition Letters, 2003, 24(4): 757-777.
[21] Raul SJE, Marcos MF, Pablo CM, et al. A theoretical framework to three-dimensional ultrasound reconstruction from irregularly sampled data [J]. Ultrasound in Medicine & Biology, 2005, 29(2): 255-269.
[22] Solberg OV, Lindseth F, Torp H, et al. Freehand 3D ultrasound reconstruction algorithms — a review [J]. Ultrasound in Medicine & Biology, 2007, 33(7): 991-1009.
[23] 孙银山,吴冬梅,杜志江,等. Freehand 3维超声重建算法综述 [J]. 中国图象图形学报, 2010, 15(11): 1561-1568.
[24] Sherebrin S, Fenster A, Rankin RN, et al. Freehand three dimensional ultrasound: implementation and applications [C] // Proceedings of the Medical Imaging 1996: Physics of Medical Imaging. Newport Beach: SPIE, 1996 : 296-303.
[25] Berg S, Torp H, Martens D, et al. Dynamic three-dimensional freehand echocardiography using raw digital ultrasound data [J]. Ultrasound in Medicine & Biology, 1999, 25(5): 745-753.
[26] Martens D, Gilja OH. The EchoPAC-3D Software for Image Analysis [M]. Singapore City: World Scientific Publishing, 2005: 305-336.
[27] Trobaugh JW, Trobaugh DJ, Richard WD. Three-dimensional imaging with stereotactic ultrasonography [J]. Computerized Medical Imaging and Graphics, 1994, 18(5): 315-323.
[28] Huang Qinghua, Lu Minhua, Zheng Yongping, et al. Speckle suppression and constrast enhancement in reconstruction of freehand 3D ultrasound images using an adaptive distance weighted method [J]. Applied Acoustics, 2009, 70(1): 21-30.
[29] Pierrick C, Pierre H, Xavier M, et al. Probe trajectory interpolation for 3D reconstruction of freehand ultrasound [J]. Preprint Submitted to Medical Image Analysis, 2007, 11(16): 604-615.
[30] Huang Qinghua, Zheng Yongping. Median filters used for volume reconstruction in freehand 3D ultrasound [C]//Proceedings of the 27th Annual Conference of the Engineering in Medicine and Biology Society. Shanghai: IEEE 2005 : 1826-1829.
[31] Huang Qinghua, Zheng Yongping. Volume reconstruction of freehand three-dimensional ultrasound using median filters [J]. Ultrasonics, 2008, 48(3): 182-192.
[32] Carr JC, Stallkamp JL, Fynes MM, et al. Design of a clinical freehand 3D ultrasound system [C]//Proceedings in the Medical Imaging 2000: Ultrasonic Imaging and Signal Processing. San Diego: SPIE, 2000 : 14-25.
[33] Nelson TR, Pretorius DH. Interactive acquisition analysis and visualization of sonographic volume data [J]. International Journal of Imaging Systems Technology, 1997, 8(1): 26-37.
[34] San R, Martín M, Alberola C, et al. Freehand ultrasound reconstruction based on ROI prior modeling and normalized convolution [C] //Proceedings of the 6th International Conference on Medical Image Computing and Computer-Assisted Intervention. Berlin: Springer, 2003 : 382-390.
[35] San R, Martin M, Caballero PP, et al. A theoretical framework to three-dimensional ultrasound reconstruction from irregularly sampled data [J]. Ultrasound in Medicine & Biology, 2003, 29(2): 255-269.
[36] Wen Tiexiang, Zhu Qingsong, Qin Wenjian, et al. An accurate and effective FMM-based approach for freehand 3D ultrasound reconstruction [J]. Biomedical Signal Processing and Control, 2013, 8 (6): 645-656.
[37] Rohling R, Gee AH, Berman L. Radial basis function interpolation for freehand 3D ultrasound [J]. 1999, 1613 : 478-483.
[38] 何琪,孙丰荣,耿俊卿,等. 基于径向基函数的超声体数据重建仿真研究 [J]. 系统仿真学报, 2010, 22(8): 1992-1996.
[39] Sanches JM, Marques JS. A rayleigh reconstruction/interpolation algorithm for 3D ultrasound [J]. Pattern Recognition Letters, 2000, 21(10): 917-926.
[40] Sanches JM, Marques JS. A multiscale algorithm for three-dimensional freehand ultrasound [J]. Ultrasound in Medicine & Biology, 2002, 28(8): 1029-1040.
[41] Chen Xiankang, Wen Tiexiang, Li Xingmin, et al. Reconstruction of freehand 3D ultrasound based on kernel regression [J]. BioMedical Engineering OnLine, 2014, 13: 124-138.
[42] Geman S, Geman D. Stochastic relaxation gibbs distributions and the bayesian restoration of images [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1984, 6(6):721-741.
[43] Kindermann R, Snell JL. Markov random fields and their applications[EB/OL].http://www.ams.org/books/conm/001/conm001- endmatter.pdf/1980/2016-08-19.
[44] Li SZ. Markov random field modeling in computer vision [M]. Berlin: Springer-Verlag, 1995.
[45] Silverman BW. Density estimation for statistics and data analysis [M]. New York: Chapman & Hall, 1986.
[46] Takeda H, Farsiu S, Milanfar P. Kernel regression for image processing and reconstruction [J]. IEEE Transactions on Image Processing, 2007, 16(2): 349-366.
[47] Rohling RN, Gee AH, Berman L. A comparation of freehand three-dimensional ultrasound reconstruction techniques [J]. Medical Image Analysis, 1999, 3(4): 339-359.
[48] 马鸣飞. 基于GPU加速的三维超声成像系统 [D]. 哈尔滨:哈尔滨工业大学, 2011.