Skip to main content

Auxiliary Disease and Treatment System of Aortic Disease Based on Mixed Reality

  • Conference paper
  • First Online:
Data Science (ICPCSEE 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 902))

  • 1720 Accesses

Abstract

With the development of science, intelligent medical technology is constantly improving. In the past, doctors were unable to perform an operation that could not correspond to the actual anatomy of the 3D and the exact anatomy of the patient. Based on the 3D reconstruction process from lesions, we combine VR and actual scene to discuss the application of mixed reality technology in the process of diagnosis and treatment of aortic disease according to the case of the auxiliary diagnosis and treatment of aortic disease [1]. Practice has proved that doctors who used our technology involved in the cross space real-time interaction with remote operation. This technology can provide a simple optimal solution for China’s medical conjoined and grading treatment system with a high efficient and low cost [2].

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Tian, J.-H., Jiang, D.: The reform of medical education in the future based on the development of virtual reality. China Manag. Informationiz. (06), 209–210 (2017)

    Google Scholar 

  2. Luo, H.-Y.: Application of VR virtual reality technology in Medical college education. Electron. Technol. Softw. Eng. (04), 10 (2017)

    Google Scholar 

  3. Xiao, X.-G.: Application of multi-slice CT scan and volume rendering reconstruction technique in lower abdominal aortic aneurysm. Chin. J. CT MRI (04), 117–119+153

    Google Scholar 

  4. Xie, C.-X., Long, T.-H., Zhao, H.-B., Deng, Y.-Y., Liao, M.-Z.: Diagnostic value of multi-slice spiral CT for acute aortic syndrome. Chin. Med. Equip. J. (07), 85–87 (2015)

    Google Scholar 

  5. Shun, Q.-L., Wang, Y., Zhao, B.-Y.: Value of MSCTA and CPR in the diagnosis of abdominal aortic aneurysm. Chin. J. Med. Guide (03), 264–265 (2015)

    Google Scholar 

  6. Ji, L.-Z., Liu, X.-P., Li, H.-T., Liu, Y.-K., Deng, Q.-C., Yang, J.-L.: The value of multislice spiral CT angiography in the diagnosis of angiogenic acute abdomen. Chin. J. Gen. Pract. (03), 443–445+505 (2015)

    Google Scholar 

  7. Yin, L.-L., Pan, Y.-X., Chen, J.-Y., Xie, H., Chen, X.-Y., Li, Y.-C.: Clinical value of dual-source CT angiography in diagnosis and following-up postoperative endovascular stent graft exclusion of abdominal aortic aneurysm. Sichuan Med. J. (02), 162–166 (2015)

    Google Scholar 

  8. Zheng, Z.-Y., Ye, Z., Huang, Y.-X., Ye, J.-L., Liu, J.-H., Huang, Y., Wang, K.-K., Zhan, H.: Factors affecting the prognosis of ruptured abdominal aortic aneurysm. Chin. J. Emerg. Med. (11), 1253–1258 (2014)

    Google Scholar 

  9. Xia, X.-L., Chen, Y., Qiu, Y.-Y., Yang, X.-J., Zhang, W.-B., Yang, Z.-Y.: Experimental study on application of 3D printing technology to print personalized vertebral body. Chin. J. Bone Joint Inj. (03), 247–250 (2016)

    Google Scholar 

  10. Huang, J.-Y., Huang, W., Hunag, F.: Effects of 64 slice spiral CT reconstruction techniques (VR, MIP) and doppler ultrasound in the diagnosis of the degree of internal carotid artery stenosis. Chin. J. CT MRI (12), 19–22 (2017)

    Google Scholar 

  11. Cai, F.-W., Hong, W.: Aortic segmentation and three-dimensional reconstruction based on CT images. J. Dongguan Univ. Technol. (05), 40–44 (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hui Gao .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Qiu, Z., Zhang, J., Gao, H. (2018). Auxiliary Disease and Treatment System of Aortic Disease Based on Mixed Reality. In: Zhou, Q., Miao, Q., Wang, H., Xie, W., Wang, Y., Lu, Z. (eds) Data Science. ICPCSEE 2018. Communications in Computer and Information Science, vol 902. Springer, Singapore. https://doi.org/10.1007/978-981-13-2206-8_2

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-2206-8_2

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2205-1

  • Online ISBN: 978-981-13-2206-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics