Real-Time 3D Ultrasound Imaging System Based on a Hybrid Reconstruction Algorithm

LYU Yifei; SHEN Yu; ZHANG Mingbo; WANG Junchen

doi:10.23919/cje.2023.00.002

Volume 33 Issue 1

Jan. 2024

Turn off MathJax

Article Contents

Article Navigation > Chinese Journal of Electronics > 2024 > 33(1): 245-255

Yifei LYU, Yu SHEN, Mingbo ZHANG, et al., “Real-Time 3D Ultrasound Imaging System Based on a Hybrid Reconstruction Algorithm,” Chinese Journal of Electronics, vol. 33, no. 1, pp. 245–255, 2024 doi: 10.23919/cje.2023.00.002

Citation:

Yifei LYU, Yu SHEN, Mingbo ZHANG, et al., “Real-Time 3D Ultrasound Imaging System Based on a Hybrid Reconstruction Algorithm,” Chinese Journal of Electronics, vol. 33, no. 1, pp. 245–255, 2024 doi: 10.23919/cje.2023.00.002

Citation:

PDF( 6225 KB)

Real-Time 3D Ultrasound Imaging System Based on a Hybrid Reconstruction Algorithm

doi: 10.23919/cje.2023.00.002

1.
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China
2.
The First Medical Center, General Hospital of Chinese PLA, Beijing 100853, China

More Information

Author Bio:
Yifei LYU received the B.E. degree in the School of Mechanical Engineering and Automation, Beihang University, Beijing, China, in 2022. In 2022, he joined Department of Mechanical Engineering, Tsinghua University, Beijing, China, as an M.E. candidate. His current research interests include medical robot and robot for rehabilitation. (Email: 15830673175@163.com)

Yu SHEN received the B.S., M.S., and Ph.D. degrees from Northwest University, Xi’an, in 2006, 2009, and 2018, respectively. She is currently a Postdoctoral Researcher with the School of Mechanical Engineering and Automation, Beihang University, Beijing, China. Her research interests include medical image computing and biosensors

Mingbo ZHANG received the M.D. degree in Peking University Health Science Center, Beijing, China, in 2010. In 2010, she joined the General Hospital of Chinese PLA, as a radiologist and researcher. In 2017, she was promoted to Associated Chief Physician and Associate Professor. Her current research interest includes application research of ultrasound guided interventional operation, ultrasound image navigation and ultrasound diagnosis and minimally invasive treatment of thyroid tumors

Junchen WANG received the B.S. and Ph.D. degrees in mechanical engineering from Beihang University, Beijing, China, in 2006 and 2012, respectively. He was a Postdoctoral Fellow with the University of Tokyo, Tokyo, Japan, from 2012 to 2016. He is currently an Associate Professor at Beihang University. He has authored more than 100 peer-reviewed articles published in international journals and conference proceedings. His research interests include medical robotics, surgical navigation, and medical image computing. (Email: wangjunchen@buaa.edu.cn)
Corresponding author: Email: wangjunchen@buaa.edu.cn
Received Date: 2023-01-02
Accepted Date: 2023-04-04

Available Online: 2023-04-24

Publish Date: 2024-01-05

Abstract

Abstract

As a safe and convenient imaging technology in clinical routine diagnosis, ultrasound imaging can provide real-time 2D images of internal tissues and organs. To realize real-time 3D image reconstruction, pixel nearest neighbor interpolation (PNN) reconstruction algorithm and Bezier interpolation algorithm are combined into a hybrid reconstruction algorithm. On this basis, a real-time interactive 3D ultrasound imaging system is developed. Through temporal calibration and spatial calibration, the six degrees of freedom poses of 2D ultrasound images can be accurately collected. The 3D volume reconstructed by the proposed 3D reconstruction algorithm is visualized by volume rendering. A multi-thread software system allows parallel operation of data acquisition, 3D reconstruction, volume visualization and other functions. 3D imaging experiments on a 3D printing femur model, a neck phantom and the neck of human volunteers were performed for systematic evaluation. When the reconstruction voxel size was set to be (0.5³ mm³, 1.0³ mm³, 1.5³ mm³), the reconstruction errors of the femur and trachea model were respectively (0.23 mm, 0.31 mm, 0.56 mm) and (0.62 mm, 0.88 mm, 1.41 mm). Clinical feasibility was demonstrated by application of the 3D ultrasound imaging on the neck of human volunteers.
- 3D ultrasound imaging,
- Free-hand reconstruction,
- Spatial calibration

FullText(HTML)

References(39)

References

[1]	S. Waldeck, S. Schmidt, C. von Falck, et al., “New hybrid multiplanar cone beam computed tomography-laser-fluoroscopic-guided approach in cochlear implant surgery,” International Journal of Computer Assisted Radiology and Surgery, vol. 17, no. 10, pp. 1837–1843, 2022. doi: 10.1007/s11548-022-02703-2
[2]	A. L. Zimerman, “The use of two-dimensional (2D), three-dimensional (3D) ultrasound and fetal Doppler studies in the first stage of labor,” in Intrapartum Ultrasonography for Labor Management, A. Malvasi, Ed. Springer, Cham, pp. 133–143, 2021.
[3]	T. T. Y. Lee, K. K. L. Lai, J. C. Y. Cheng, et al., “3D ultrasound imaging provides reliable angle measurement with validity comparable to X-ray in patients with adolescent idiopathic scoliosis,” Journal of Orthopaedic Translation, vol. 29, pp. 51–59, 2021. doi: 10.1016/j.jot.2021.04.007
[4]	F. Cenni, S. H. Schless, L. Bar-On, et al., “Reliability of a clinical 3D freehand ultrasound technique: analyses on healthy and pathological muscles,” Computer Methods and Programs in Biomedicine, vol. 156, pp. 97–103, 2018. doi: 10.1016/j.cmpb.2017.12.023
[5]	M. Mozaffarzadeh, M. Soozande, F. Fool, et al., “Receive/transmit aperture selection for 3D ultrasound imaging with a 2D matrix transducer,” Applied Sciences, vol. 10, no. 15, article no. 5300, 2020. doi: 10.3390/app10155300
[6]	E. Hayashi, N. Kanno, R. Shintate, et al., “3D ultrasound imaging by synthetic transmit aperture beamforming using a spherically curved array transducer,” Japanese Journal of Applied Physics, vol. 61, no. SG, article no. SG1034, 2022. doi: 10.35848/1347-4065/AC51C1
[7]	R. J. Housden, A. H. Gee, G. M. Treece, et al., “Sensorless reconstruction of unconstrained freehand 3D ultrasound data,” Ultrasound in Medicine & Biology, vol. 33, no. 3, pp. 408–419, 2007. doi: 10.1016/j.ultrasmedbio.2006.09.015
[8]	H. T. Guo, S. Xu, B. Wood, et al., “Sensorless freehand 3D ultrasound reconstruction via deep contextual learning,” in Proceedings of the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, Lima, Peru, pp. 463–472, 2020.
[9]	R. Prevost, M. Salehi, S. Jagoda, et al., “3D freehand ultrasound without external tracking using deep learning,” Medical Image Analysis, vol. 48, pp. 187–202, 2018. doi: 10.1016/j.media.2018.06.003
[10]	H. Moon, G. Ju, S. Park, et al., “3D freehand ultrasound reconstruction using a piecewise smooth Markov random field,” Computer Vision and Image Understanding, vol. 151, pp. 101–113, 2016. doi: 10.1016/j.cviu.2015.12.009
[11]	M. I. Daoud, A. L. Alshalalfah, F. Awwad, et al., “Freehand 3D ultrasound imaging system using electromagnetic tracking,” in Proceedings of 2015 International Conference on Open Source Software Computing, Amman, Jordan, pp. 1–5, 2015.
[12]	Z. P. Chen and Q. H. Huang, “Real-time freehand 3D ultrasound imaging,” Computer Methods in Biomechanics and Biomedical Engineering:Imaging & Visualization, vol. 6, no. 1, pp. 74–83, 2018. doi: 10.1080/21681163.2016.1167623
[13]	J. Meza, S. H. Contreras-Ortiz, L. A. Romero, et al., “Three-dimensional multimodal medical imaging system based on freehand ultrasound and structured light,” Optical Engineering, vol. 60, no. 5, article no. 054106, 2021. doi: 10.1117/1.OE.60.5.054106
[14]	Q. H. Huang, J. L. Lan, and X. L Li, “Robotic arm based automatic ultrasound scanning for three-dimensional imaging,” IEEE Transactions on Industrial Informatics, vol. 15, no. 2, pp. 1173–1182, 2018. doi: 10.1109/TII.2018.2871864
[15]	M. Victorova, D. Navarro-Alarcon, and Y. P. Zheng, “3D ultrasound imaging of scoliosis with force-sensitive robotic scanning,” in Proceedings of the 2019 Third IEEE International Conference on Robotic Computing (IRC), Naples, Italy, pp. 262–265, 2019.
[16]	F. Suligoj, C. M. Heunis, J. Sikorski, et al., “Robust – An autonomous robotic ultrasound system for medical imaging,” IEEE Access, vol. 9, pp. 67456–67465, 2021. doi: 10.1109/ACCESS.2021.3077037
[17]	J. Qi, M. Y. Ding, and M. Yuchi, “3D ultrasound data acqusition system based on back end scan mode,” in Proceedings of 2011 International Conference on Intelligent Computation and Bio-Medical Instrumentation, Wuhan, China, pp. 156–158, 20118.
[18]	C. Y. Xu, G. P. Li, Q. H. Huang, et al., “Establishment of a 3D ultrasound imaging system based on pulse-triggered image acquisition,” Journal of Southern Medical University, vol. 41, no. 5, pp. 767–774, 2021. (in Chinese) doi: 10.12122/j.issn.1673-4254.2021.05.19
[19]	V. S. Chan, F. Mohamed, Y. A. Yusoff, et al., “Using game controller as position tracking sensor for 3D freehand ultrasound imaging,” Medical & Biological Engineering & Computing, vol. 58, no. 5, pp. 889–902, 2020. doi: 10.1007/s11517-019-02044-4
[20]	Q. Q. Cai, C. Peng, J. Y. Lu, et al., “Performance enhanced ultrasound probe tracking with a hemispherical marker rigid body,” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 68, no. 6, pp. 2155–2163, 2021. doi: 10.1109/TUFFC.2021.3058145
[21]	A. Lang, P. Mousavi, G. Fichtinger, et al., “Fusion of electromagnetic tracking with speckle-tracked 3d freehand ultrasound using an unscented Kalman filter,” in Proceedings of SPIE 7265, Medical Imaging 2009: Ultrasonic Imaging and Signal Processing, Lake Buena Vista, Florida, USA, article no.72651A, 2009.
[22]	T. R. Nelson and D. H. Pretorius, “Interactive acquisition, analysis, and visualization of sonographic volume data,” International Journal of Imaging Systems and Technology, vol. 8, no. 1, pp. 26–37, 1997. doi: 10.1002/(SICI)1098-1098(1997)8:1<26::AID-IMA4>3.0.CO;2-V
[23]	D. G. Gobbi and T. M. Peters, “Interactive intra-operative 3D ultrasound reconstruction and visualization,” in Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention, Tokyo, Japan, pp. 156–163, 2002.
[24]	Q. H. Huang, Y. P. Zheng, M. H. Lu, et al., “Development of a portable 3d ultrasound imaging system for musculoskeletal tissues,” Ultrasonics, vol. 43, no. 3, pp. 153–163, 2005. doi: 10.1016/j.ultras.2004.05.003
[25]	S. Sherebrin, A. Fenster, R. N. Rankin, et al., “Freehand three-dimensional ultrasound: implementation and applications,” in Proceedings of SPIE 2708, Medical Imaging 1996: Physics of Medical Imaging, Newport Beach, CA, USA, pp. 296–303, 1996.
[26]	J. W. Trobaugh, D. J. Trobaugh, and W. D. Richard, “Three-dimensional imaging with stereotactic ultrasonography,” Computerized Medical Imaging and Graphics, vol. 18, no. 5, pp. 315–323, 1994. doi: 10.1016/0895-6111(94)90002-7
[27]	R. Rohling, A. Gee, and L. Berman, “A comparison of freehand three-dimensional ultrasound reconstruction techniques,” Medical Image Analysis, vol. 3, no. 4, pp. 339–359, 1999. doi: 10.1016/S1361-8415(99)80028-0
[28]	Q. H. Huang, Y. P. Huang, W. Hu, et al., “Bezier interpolation for 3-D freehand ultrasound,” IEEE Transactions on Human-Machine Systems, vol. 45, no. 3, pp. 385–392, 2015. doi: 10.1109/THMS.2014.2374551
[29]	H. B. Chen, R. Zheng, E. Lou, et al., “Compact and wireless freehand 3D ultrasound real-time spine imaging system: A pilot study,” in Proceedings of the 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Montreal, Canada, pp. 2105–2108, 2020.
[30]	W. W. Jiang, X. T. Chen, and C. H. Yu, “A real-time freehand 3D ultrasound imaging method for scoliosis assessment,” Journal of Applied Clinical Medical Physics, vol. 23, no. 8, article no. e13709, 2022. doi: 10.1002/ACM2.13709
[31]	S. W. Xing, D. W. Cool, L. Gardi, et al., “A 2D/3D US/CT-guided system for percutaneous focal liver thermal ablation,” in Proceedings of SPIE 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, San Diego, CA, USA, article no.1203413, 2022.
[32]	T. X. Wen, C. Wang, Y. Zhang, et al., “A novel ultrasound probe spatial calibration method using a combined phantom and stylus,” Ultrasound in Medicine & Biology, vol. 46, no. 8, pp. 2079–2089, 2020. doi: 10.1016/j.ultrasmedbio.2020.03.018
[33]	Y. F. Lv, Y. Ning, Y. Shen, et al., “A real-time interactive 3D ultrasound imaging system,” in Proceedings of 2022 WRC Symposium on Advanced Robotics and Automation (WRC SARA), Beijing, China, pp. 113–119, 2022.
[34]	F. Rousseau, P. Hellier, and C. Barillot, “A novel temporal calibration method for 3-D ultrasound,” IEEE Transactions on Medical Imaging, vol. 25, no. 8, pp. 1108–1112, 2006. doi: 10.1109/TMI.2006.877097
[35]	P. W. Hsu, G. M. Treece, R. W. Prager, et al., “Comparison of freehand 3-D ultrasound calibration techniques using a stylus,” Ultrasound in Medicine & Biology, vol. 34, no. 10, pp. 1610–1621, 2008. doi: 10.1016/j.ultrasmedbio.2008.02.015
[36]	K. S. Arun, T. S. Huang, and S. D. Blostein, “Least-squares fitting of two 3-D point sets,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-9, no. 5, pp. 698–700, 1987. doi: 10.1109/TPAMI.1987.4767965
[37]	Q. H. Huang and Z. Z. Zeng, “A review on real-time 3D ultrasound imaging technology,” BioMed Research International, vol. 2017, article no. 6027029, 2017. doi: 10.1155/2017/6027029
[38]	T. R. Nelson and D. H. Pretorius, “Three-dimensional ultrasound imaging,” Ultrasound in Medicine & Biology, vol. 24, no. 9, pp. 1243–1270, 1998. doi: 10.1016/S0301-5629(98)00043-X
[39]	S. Virga, O. Zettinig, M. Esposito, et al., “Automatic force-compliant robotic ultrasound screening of abdominal aortic aneurysms,” in Proceedings of 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, pp. 508–513, 2016.