Skip to main content

VeLight: A 3D virtual reality tool for CT-based anatomy teaching and training

Abstract

For doctors and other medical professionals, the human body is the focus of their daily practice. A solid understanding of how it is built up, that is, the anatomy of the human body, is essential to ensure safe medical practice. Current anatomy education takes place either using text books or via dissecting human cadavers, with text books being the most traditional way to learn anatomy due to the cost of the alternatives. However, printed media offer only a 2D perception of a part of the human body. Although dissection of human cadavers can give a more direct observation and interaction with human bodies, it is extremely costly because of the need of preserving human bodies and maintaining dissection rooms. To solve this issue, we developed VeLight, a system with which students can learn anatomy based on CT datasets using a 3D Virtual Reality display (zSpace). VeLight offers simple and intuitive interactions, and allows teachers to design their own courses using their own material. The system offers an interactive, depth-perceptive learning experience and improves the learning process. We conducted an informal user study to validate the effectiveness of VeLight. The results show that participants were able to learn and remember how to work with VeLight very quickly. All participants reported enthusiasm for the potential of VeLight in the domain of medical education.

Graphic Abstract

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Notes

  1. 1.

    https://zspace.com/.

  2. 2.

    https://3d4medical.com/.

  3. 3.

    https://www.microsoft.com/en-us/hololens.

  4. 4.

    https://openscenegraph.com/.

References

  1. Akers D 2006. Cinch: A cooperatively designed marking interface for 3d pathway selection. In Proceedings of the 19th Annual ACM Symposium on User Interface Software and Technology, UIST ’06, pp. 33–42. ACM, New York, NY, USA, https://doi.org/10.1145/1166253.1166260

  2. Azer SA, Eizenberg N (2007) Do we need dissection in an integrated problem-based learning medical course? perceptions of first- and second-year students. Surg Radiol Anat 29:173–180

    Article  Google Scholar 

  3. Aziz MA, Mckenzie JC, Wilson JS, Cowie RJ, Ayeni SA, Dunn BK (2002) The human cadaver in the age of biomedical informatics. Anatom Record 269(1):20–32. https://doi.org/10.1002/ar.10046

    Article  Google Scholar 

  4. Bach B, Dachselt R, Carpendale S, Dwyer T, Collins C, Lee B 2016. Immersive analytics: Exploring future interaction and visualization technologies for data analytics. In Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces, ISS ’16, pp. 529–533. ACM, New York, NY, USA, https://doi.org/10.1145/2992154.2996365

  5. Besançon L, Ynnerman A, Keefe DF, Yu L, Isenberg T (2021) The state of the art of spatial interfaces for 3d visualization. Comput Graphics Forum 40(1):293–326. https://doi.org/10.1111/cgf.14189

    Article  Google Scholar 

  6. Blum T, Kleeberger V, Bichlmeier C, Navab N 2012. mirracle: An augmented reality magic mirror system for anatomy education. In IEEE Virtual Reality Workshops, pp. 115–116, https://doi.org/10.1109/VR.2012.6180909

  7. Bockers A, Jerg-Bretzke L, Lamp C, Brinkmann A, Traue HC, Bockers TM (2010) The gross anatomy course: an analysis of its importance. Anatom Sci Edu 3(1):3–11. https://doi.org/10.1002/ase.124

    Article  Google Scholar 

  8. Drake RL, McBride JM, Lachman N, Pawlina W (2009) Medical education in the anatomical sciences: the winds of change continue to blow. Anatom Sci Edu 2(6):253–259. https://doi.org/10.1002/ase.117

    Article  Google Scholar 

  9. Estai M, Bunt S (2016) Best teaching practices in anatomy education: a critical review. Ann Anatom - Anatomischer Anzeiger 208:151–157. https://doi.org/10.1016/j.aanat.2016.02.010

    Article  Google Scholar 

  10. Fruhstorfer B, Palmer J, Brydges S, Abrahams P (2011) The use of plastinated prosections for teaching anatomy-the view of medical students on the value of this learning resource. Clin Anatom 24(2):246–252. https://doi.org/10.1002/ca.21107

    Article  Google Scholar 

  11. Fu C.-W., Goh W.-B., Ng J. A. 2010. Multi-touch techniques for exploring large-scale 3d astrophysical simulations. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’10, pp. 2213–2222. ACM, New York, NY, USA, https://doi.org/10.1145/1753326.1753661

  12. Fyfe G, Fyfe S, Dye D, Crabb H (2013) Use of Anatomage tables in a large first year core unit. In: 30th Annual conference on Australian Society for Computers in Learning in Tertiary Education, ASCILITE 2013, pp 298–302

  13. Glas H, Kraeima J, van Ooijen P, Spijkervet F, Yu L, Witjes M (2021) Augmented reality visualization for image-guided surgery: a validation study using a three-dimensional printed phantom. J Oral Maxillofac Surg. https://doi.org/10.1016/j.joms.2021.04.001

    Article  Google Scholar 

  14. Jackson B, Lau TY, Schroeder D, Toussaint KC, Keefe DF (2013) A lightweight tangible 3d interface for interactive visualization of thin fiber structures. IEEE Trans Visual Comput Graph 19(12):2802–2809. https://doi.org/10.1109/TVCG.2013

    Article  Google Scholar 

  15. Johnson S, Jackson B, Tourek B, Molina M, , Erdman A. G., Keefe D. F. 2016 Immersive analytics for medicine: Hybrid 2d/3d sketch-based interfaces for annotating medical data and designing medical devices. Immersive Analytics: Exploring Future Interaction and Visualization Technologies for Data Analytics, Workshop at IIS 2016,

  16. Kalavakonda N, Sekhar L, Hannaford B 2019. Augmented reality application for aiding tumor resection in skull-base surgery. In 2019 International Symposium on Medical Robotics (ISMR), pp. 1–6, https://doi.org/10.1109/ISMR.2019.8710203

  17. Keefe DF (2010) Integrating visualization and interaction research to improve scientific workflows. IEEE Comput Graph Appl 30:8–13. https://doi.org/10.1109/MCG.2010.30

    Article  Google Scholar 

  18. Keefe DF, Isenberg T (2013) Reimagining the scientific visualization interaction paradigm. Computer 46(5):51–57. https://doi.org/10.1109/MC.2013.178

    Article  Google Scholar 

  19. Khadka R, Money J, Banić A 2018. Body-prop interaction: Augmented open discs and egocentric body-based interaction for exploring immersive visualizations. In Proc. ISS, pp. 327–332. ACM, New York, https://doi.org/10.1145/3279778.3281458

  20. Khot Z, Quinlan K, Norman GR, Wainman B (2013) The relative effectiveness of computer-based and traditional resources for education in anatomy. Anatom Sci Edu 6(4):211–215. https://doi.org/10.1002/ase.1355

    Article  Google Scholar 

  21. Kim K, Lawrence R. L., Kyllonen N, Ludewig P. M., Ellingson A. M., Keefe D. F. 2017 Poster: Anatomical 2d/3d shape-matching in virtual reality: A user interface for quantifying joint kinematics with radiographic imaging. IEEE Symposium on 3D User Interfaces, March

  22. Korf H-W, Wicht H, Snipes RL, Timmermans J-P, Paulsen F, Rune G, Baumgart-Vogt E (2008) The dissection course - necessary and indispensable for teaching anatomy to medical students. Ann Anatom - Anatomischer Anzeiger 190(1):16–22. https://doi.org/10.1016/j.aanat.2007.10.001

    Article  Google Scholar 

  23. Kreylos O, Bawden G, Bernardin T, Billen M. I., Cowgill E. S., Gold R. D., Hamann B, Jadamec M, Kellogg L. H., Staadt O. G., Sumner D. Y. 2006. Enabling scientific workflows in virtual reality. In Proceedings of the 2006 ACM International Conference on Virtual Reality Continuum and Its Applications, VRCIA ’06, pp. 155–162. ACM, New York, NY, USA, https://doi.org/10.1145/1128923.1128948

  24. Mathur A. S. 2015. Low cost virtual reality for medical training. In 2015 IEEE Virtual Reality (VR), pp. 345–346, March https://doi.org/10.1109/VR.2015.7223437

  25. McNulty JA, Halama J, Espiritu B (2003) Evaluation of computer-aided instruction in the medical gross anatomy curriculum. Clin Anatom 17(1):73–78. https://doi.org/10.1002/ca.10188

    Article  Google Scholar 

  26. McNulty JA, Sonntag B, Sinacore JM (2009) Evaluation of computer-aided instruction in a gross anatomy course: a six-year study. Anatom Sci Edu 2(1):2–8. https://doi.org/10.1002/ase.66

    Article  Google Scholar 

  27. Meulstee JW, Nijsink J, Schreurs R, Verhamme LM, Xi T, Delye HHK, Borstlap WA, Maal TJJ (2019) Toward holographic-guided surgery. Surg Innov 26(1):86–94. https://doi.org/10.1177/1553350618799552

    Article  Google Scholar 

  28. Mildenberger P, Eichelberg M, Martin E (2002) Introduction to the dicom standard. Euro Radiol 12(4):920–927. https://doi.org/10.1007/s003300101100

    Article  Google Scholar 

  29. Mischkowski R, Zinser M, Kübler A, Seifert U, Zöller J 2005. Clinical and experimental evaluation of an augmented reality system in cranio-maxillofacial surgery. International Congress Series, 1281(Supplement C):565 – 570, CARS 2005: Computer Assisted Radiology and Surgery. https://doi.org/10.1016/j.ics.2005.03.277

  30. Moxham B, Plaisant O (2007) Perception of medical students towards the clinical relevance of anatomy. Clin Anatom 20(5):560–564. https://doi.org/10.1002/ca.20453

    Article  Google Scholar 

  31. Netterstrom I, Kayser L (2008) Learning to be a doctor while learning anatomy. Anatom Sci Edu 1(4):154–158. https://doi.org/10.1002/ase.31

    Article  Google Scholar 

  32. Pabst R (2009) Anatomy curriculum for medical students: What can be learned for future curricula from evaluations and questionnaires completed by students, anatomists and clinicians in different countries? Ann Anatom - Anatomischer Anzeiger 191(6):541–546. https://doi.org/10.1016/j.aanat.2009.08.007

    MathSciNet  Article  Google Scholar 

  33. Park C. H., Wilson K. L., Howard A. M. 2014. Pilot study: Supplementing surgical training for medical students using a low-cost virtual reality simulator. In 2014 IEEE 27th International Symposium on Computer-Based Medical Systems, pp. 125–127, May https://doi.org/10.1109/CBMS.2014.74

  34. Ramnarayan K, Hande S (2005) Thoughts on self directed learning in medical schools: Making students more responsible. New Horizons 11(3)

  35. Reeves RE, Aschenbrenner JE, Wordinger RJ, Roque RS, Sheedlo HJ (2004) Improved dissection efficiency in the human gross anatomy laboratory by the integration of computers and modern technology. Clin Anatom 17(4):337–344. https://doi.org/10.1002/ca.10245

    Article  Google Scholar 

  36. Rizzolo LJ, Stewart WB (2006) Should we continue teaching anatomy by dissection when...? Anatom Record Part B New Anatom 289B(6):215–218. https://doi.org/10.1002/ar.b.20117

    Article  Google Scholar 

  37. Sotiropoulos F, Erdman AG, Borazjani I, Malbraaten N, Le TB, Coffey D, Keefe DF (2012) Interactive slice wim: navigating and interrogating volume data sets using a multisurface, multitouch VR interface. IEEE Trans Visual Comput Graph 18:1614–1626. https://doi.org/10.1109/TVCG.2011.283

    Article  Google Scholar 

  38. Sousa M, Mendes D, Paulo S, Matela N, Jorge J, Lopes D. S. o. 2017. VRRRRoom: Virtual reality for radiologists in the reading room. In Proc. CHI, pp. 4057–4062. ACM, New York, https://doi.org/10.1145/3025453.3025566

  39. Tam M, Hart A, Williams S, Holland R, Heylings D, Leinster S (2010) Evaluation of a computer program (‘disect’) to consolidate anatomy knowledge: a randomised-controlled trial. Med Teacher 32(3):e138–e142. https://doi.org/10.3109/01421590903144110

    Article  Google Scholar 

  40. Theart RP, Loos B, Niesler TR (2017) Virtual reality assisted microscopy data visualization and colocalization analysis. BMC Bioinform 18(2):1–16. https://doi.org/10.1186/s12859

    Article  Google Scholar 

  41. Turney BW (2007) Anatomy in a modern medical curriculum. Ann Royal College Surg Engl 89(2):104–107. https://doi.org/10.1308/003588407X168244

    Article  Google Scholar 

  42. Wang J, Wu J, Cao A, Zhou Z, Zhang H, Wu Y (2021) Tac-miner: Visual tactic mining for multiple table tennis matches. IEEE Trans Vis Comput Graph 27(6):2770–2782. https://doi.org/10.1109/TVCG.2021.3074576

    Article  Google Scholar 

  43. Ware C (2004) Inform Visual: Percep Des. Morgan Kaufmann Publishers Inc., San Francisco

    Google Scholar 

  44. Wu H-K, Lee SW-Y, Chang H-Y, Liang J-C (2013) Current status, opportunities and challenges of augmented reality in education. Comput Edu 62:41–49. https://doi.org/10.1016/j.compedu.2012.10.024

    Article  Google Scholar 

  45. Xie X, Wang J, Liang H, Deng D, Cheng S, Zhang H, Chen W, Wu Y (2021) Passvizor: Toward better understanding of the dynamics of soccer passes. IEEE Trans Vis Comput Graph 27(2):1322–1331. https://doi.org/10.1109/TVCG.2020.3030359

    Article  Google Scholar 

  46. Ye S, Chen Z, Chu X, Wang Y, Fu S, Shen L, Zhou K, Wu Y (2021) Shuttlespace: Exploring and analyzing movement trajectory in immersive visualization. IEEE Trans Vis Comput Graph 27(2):860–869

    Article  Google Scholar 

  47. Yu L, Efstathiou K, Isenberg P, Isenberg T (2012) Efficient structure-aware selection techniques for 3D point cloud visualizations with 2DOF input. IEEE Trans Vis Comput Graph 18(12):2245–2254. https://doi.org/10.1109/TVCG.2012.217

    Article  Google Scholar 

  48. Yu L, Efstathiou K, Isenberg P, Isenberg T (2016) CAST: Effective and efficient user interaction for context-aware selection in 3D particle clouds. IEEE Trans Vis Comput Graph 22(1):886–895. https://doi.org/10.1109/TVCG.2015.2467202

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to thank all the participants who joined in the preliminary user study and the discussions. L. Yu is supported by XJTLU Research Development Funding RDF-19-02-11.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Lingyun Yu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (MP4 69,920 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yu, L., Ouwerling, J., Svetachov, P. et al. VeLight: A 3D virtual reality tool for CT-based anatomy teaching and training. J Vis (2021). https://doi.org/10.1007/s12650-021-00790-y

Download citation

Keywords

  • 3D manipulation
  • Spatial interaction
  • Anatomy teaching
  • Medical education