Journal of Information Processing Systems

  • 제20권4호
  • /
  • Pages.418-431
  • /
  • 2024
  • /
  • 1976-913X(pISSN)
  • /
  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
권호 표지
DOI QR코드

DOI QR Code

A Survey on VR-Based Annotation of Medical Images

  • Mika Anttonen (Dept. of Computer Science and Engineering, Seoul National University of Science and Technology) ;
  • Dongwann Kang (Dept. of Computer Science and Engineering, Seoul National University of Science and Technology)
  • 투고 : 2022.05.27
  • 심사 : 2022.08.10
  • 발행 : 2024.08.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

The usage of virtual reality (VR) in healthcare field has been gaining attention lately. The main use cases revolve around medical imaging and clinical skill training. Healthcare professionals have found great benefits in these cases when done in VR. While medical imaging on the desktop has lots of available software with various tools, VR versions are mostly stripped-down with only basic tools. One of the many tool groups significantly missing is annotation. In this paper, we survey the current situation of medical imaging software both on the desktop and in the VR environment. We will discuss general information on medical imaging and provide examples of both desktop and VR applications. We will also discuss the current status of annotation in VR, the problems that need to be overcome and possible solutions for them. The findings of this paper should help developers of future medical image annotation tools in choosing which problem they want to tackle and possible methods. The findings will be used to help in our future work of developing annotation tools.

키워드

과제정보

This study was supported by the Research Program funded by the Seoul National University of Science and Technology (SeoulTech).

참고문헌

  1. Meta, "Oculus Rift S and Rift minimum requirements and system specifications," c2024 [Online]. Available: https://www.meta.com/help/quest/articles/headsets-and-accessories/oculus-rift-s/rift-s-minimumrequirements/.
  2. D. Velev and P. Zlateva, "Analysis of v-commerce as the new online sales channel," International Journal of e-Education, e-Business, e-Management and e-Learning, vol. 9, no. 2, pp. 131-137, 2019. http://dx.doi.org/10.17706/ijeeee.2019.9.2.131-137
  3. Program-Ace, "Virtual reality (VR) market statistics and trends," 2017 [Online]. Available: https://programace.com/blog/vr-market-statistics-and-trends/.
  4. W. D. Bidgood, S. C. Horii, F. W. Prior, and D. E. Van Syckle, "Understanding and using DICOM, the data interchange standard for biomedical imaging," Journal of the American Medical Informatics Association, vol. 4, no. 3, pp. 199-212, 1997. https://doi.org/10.1136/jamia.1997.0040199
  5. Neuroimaging Informatics Technology Initiative, "NIfTI documentation," 2007 [Online]. Available: https://nifti.nimh.nih.gov/nifti-1/documentation/.
  6. R. A. Robb, D. P. Hanson, R. A. Karwoski, A. G. Larson, E. L. Workman, and M. C. Stacy, "Analyze: a comprehensive, operator-interactive software package for multidimensional medical image display and analysis," Computerized Medical Imaging and Graphics, vol. 13, no. 6, pp. 433-454, 1989. https://doi.org/10.1016/0895-6111(89)90285-1
  7. McConnell Brain Imaging Center, "MINC library and tools," c2016 [Online]. Available: http://www.bic.mni.mcgill.ca/ServicesSoftware/MINC.
  8. M. Larobina and L. Murino, "Medical image file formats," Journal of Digital Imaging, vol. 27, pp. 200-206, 2014. https://doi.org/10.1007/s10278-013-9657-9
  9. Innolitics, "DICOM Standard Browser," 2024 [Online]. Available: https://dicom.innolitics.com/ciods.
  10. T. Dutta-Roy, "Medical image analysis with deep learning - IV," 2024 [Online]. Available: https://medium.com/@taposhdr/medical-image-analysis-with-deep-learning-iv-479b5fa446e7.
  11. MedDream, "DICOM Viewer's online demo," 2024 [Online]. Available: https://www.softneta.com/onlinedicom-viewer/.
  12. A. Weston, "Understanding DICOM," 2020 [Online]. Available: https://towardsdatascience.com/understanding-dicom-bce665e62b72.
  13. Radiopaedia, "Hounsfield unit," 2024 [Online]. Available: https://radiopaedia.org/articles/hounsfield-unit.
  14. MicroDicom, "MicroDicom - free DICOM viewer for Windows" 2024 [Online]. AVailabler: https://www.microdicom.com/.
  15. "3D Slicer, a free open-source software," 2024 [Online]. Available: https://www.slicer.org/.
  16. Radiopaedia, "Cross-sectional imaging," 2021 [Online]. Available: https://radiopaedia.org/articles/crosssectional-imaging-1.
  17. MITK's Wiki, "The Medical Imaging Interaction Toolkit (MITK)," 2024 [Online]. Available: https://www.mitk.org/wiki/The_Medical_Imaging_Interaction_Toolkit_(MITK).
  18. VTK's Wiki, "The Visualization ToolKit (VTK)," 2021 [Online]. Available: https://vtk.org/Wiki/VTK.
  19. H. Hoffman and D. Vu, "Virtual reality: teaching tool of the twenty-first century?," Academic Medicine, vol. 72, no. 12, pp. 1076-1081, 1997. https://doi.org/10.1097/00001888-199712000-00018
  20. R. N. Uppot, B. Laguna, C. J. McCarthy, G. De Novi, A. Phelps, E. Siegel, and J. Courtier, "Implementing virtual and augmented reality tools for radiology education and training, communication, and clinical care," Radiology, vol. 291, no. 3, pp. 570-580, 2019. https://doi.org/10.1148/radiol.2019182210
  21. T. Timonen, A. Dietz, P. Linder, A. Lehtimaki, H. Lopponen, A. P. Elomaa, and M. Iso-Mustajarvi, "The effect of virtual reality on temporal bone anatomy evaluation and performance," European Archives of Oto- Rhino-Laryngology, vol. 279, no. 9, pp. 4303-4312, 2022. https://doi.org/10.1007/s00405-021-07183-9
  22. Medicalholodeck, "Medical Imaging XR," c2023 [Online]. Available: https://www.medicalholodeck.com/en/surgical-planning-training-digital-twins-augmented-virtual-reality/.
  23. M. El Beheiry, C. Godard, C. Caporal, V. Marcon, C. Ostertag, S. Doutreligne, et al., "DIVA Viewer User Manual," 2017 [Online]. Available: https://diva.pasteur.fr/wp-content/uploads/2019/09/diva-viewer-manual.pdf.
  24. C. Guerinot, V. Marcon, C. Godard, T. Blanc, H. Verdier, G. Planchon, G., ... & Masson, J. B. (2022). "New approach to accelerated image annotation by leveraging virtual reality and cloud computing," Frontiers in Bioinformatics, vol. 1, article no. 777101, 2022. https://doi.org/10.3389/fbinf.2021.777101
  25. SurgeryVision, "SurgeryVision - Surgery planning in virtual reality," 2022 [Online]. Available: https://www.surgeryvision.com/.
  26. Wikipedia, "Marching cubes," 2024 [Online]. Available: https://en.wikipedia.org/wiki/Marching_cubes.
  27. R. Prehn, "Unity Tip: combine meshes for performance and organization" 2017 [Online]. Available: https://medium.com/acrossthegalaxy/unity-tip-combine-meshes-for-performance-and-organization-c3515c844fdb.
  28. J. K. Udupa, H. M. Hung, and K. S. Chuang, "Surface and volume rendering in three-dimensional imaging: a comparison," Journal of Digital Imaging, vol. 4, pp. 159-168, 1991. https://doi.org/10.1007/BF03168161
  29. IrisVR "The importance of frame rates," c2024 [Online]. Available: https://help.irisvr.com/hc/en-us/articles/215884547-The-Importance-of-Frame-Rates.
  30. NVIDIA, "NVIDIA Clara Train SDK v4.1," 2023 [Online]. Available: https://docs.nvidia.com/clara/claratrain-sdk/index.html.