Skip to main content

3D Imaging

  • Chapter
  • First Online:
  • 783 Accesses

Abstract

Over the years, digital photography in dermatology has been proven to be an indispensable tool for documenting various diseases for clinical, scientific, didactic, and medico-legal aims, for archiving and for medical-scientific communication. Three-dimensional imaging is a new branch of digital photography with countless advantages. Thanks to specific software, the elaboration of the image allows to evaluate in an objective way the pigmentation, the vascular characteristics, and the skin texture and to measure areas and volumes. The observation of the photographic images is of paramount importance both for a correct diagnosis aimed at the choice of the best therapeutic approach and for a correct evaluation in follow-up, through the comparison between the images “before and after.” The fields of application are from clinical medicine to surgery, from esthetics to the prevention of skin tumors. Today the focus is on new 3D systems that allow to store, to analyze, and to reproduce healthy and pathological skin in a more detailed way and in accordance with reality.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   49.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   64.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   99.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

References

  1. Rajadhyaksha M, Grossman M, Esterowitz D, Webb RH, Anderson RR. In vivo confocal scanning laser microscopy of human skin: melanin provides strong contrast. J Invest Dermatol. 1995;104:946–52.

    CAS  PubMed  Google Scholar 

  2. Jasaitiene D, et al. Principles of high-frequency ultrasonography for investigation of skin pathology. J Eur Acad Dermatol Venereol JEADV. 2011;25:375–82.

    CAS  PubMed  Google Scholar 

  3. Cal K, Stefanowska J, Zakowiecki D. Current tools for skin imaging and analysis. Int J Dermatol. 2009;48:1283–9.

    PubMed  Google Scholar 

  4. Breunig HG, Studier H, König K. Multiphoton excitation characteristics of cellular fluorophores of human skin in vivo. Opt Express. 2010;18:7857–71.

    CAS  PubMed  Google Scholar 

  5. Skvara H, et al. Quantification of skin lesions with a 3D stereovision camera system: validation and clinical applications. Skin Res Technol. 2013;19:e182–90.

    PubMed  Google Scholar 

  6. Ort R, et al. The reliability of a three-dimensional photo system- (3dMDface-) based evaluation of the face in cleft lip infants. Plast Surg Int. 2012;2012:1–8.

    Google Scholar 

  7. Guillard G, Lagarde J. Skin lesions segmentation and quantification from 3D body’s models. Skin Res Technol Off J Int Soc Bioeng Skin ISBS Int Soc Digit Imaging Skin ISDIS Int Soc Skin Imaging ISSI. 2005;11:123–31.

    CAS  Google Scholar 

  8. Zhou Y, Smith M, Smith L, Warr R. Using 3D differential forms to characterize a pigmented lesion in vivo. Skin Res Technol. 2010;16:77–84.

    PubMed  Google Scholar 

  9. Richmond C. Sir Godfrey Hounsfield. BMJ. 2004;329:687.

    PubMed Central  Google Scholar 

  10. Damadian R. Tumor detection by nuclear magnetic resonance. Science. 1971;171:1151–3.

    CAS  PubMed  Google Scholar 

  11. Geng J. Structured-light 3D surface imaging: a tutorial. Adv Opt Phot. 2011;3:128e60.

    Google Scholar 

  12. Thalmaan D. Die Stereogrammetrie: ein diagnostisches Hilfsmittel in der Kieferorthopaedie [Stereophotogrammetry: a diagnostic device in orthodontology]. Zurich: University Zurich, Switzerland; 1944.

    Google Scholar 

  13. Burke PH, Beard FH. Stereophotogrammetry of the face. A preliminary investigation into the accuracy of a simplified system evolved for contour mapping by photography. Am J Orthod. 1967;53:769e82.

    Google Scholar 

  14. Neely JG, Cheung JY, Wood M, Byers J, Rogerson A. Computerized quantitative dynamic analysis of facial motion in the paralyzed and synkinetic face. Am J Otol. 1992;13:97–107.

    CAS  PubMed  Google Scholar 

  15. Takasaki H. Moire topography. Appl Opt. 1970;9:1467–72.

    CAS  PubMed  Google Scholar 

  16. Saito N, Nishijima T, Fujimura T, Moriwaki S, Takema Y. Development of a new evaluation method for cheek sagging using a Moire 3D analysis system. Skin Res Technol. 2008;14:287–92.

    PubMed  Google Scholar 

  17. Inokuchi I, Sato K, Ozaki Y. Range-imaging system for 3-D range imaging. Paper presented at: 7th ICPR Proceeding; Montreal, Canada. 1984. p.806.

    Google Scholar 

  18. Meier-Gallati V, Scriba H, Fisch U. Objective scaling of facial nerve function based on area analysis (OSCAR). Otolaryngol Head Neck Surg. 1998;118:545e50.

    Google Scholar 

  19. Bush K, Antonyshyn O. Three-dimensional facial anthropometry using a laser surface scanner: validation of the technique. Plast Reconstr Surg. 1996;98:226e35.

    Google Scholar 

  20. Geng ZJ. Rainbow three-dimensional camera: new concept of high-speed three-dimensional vision systems. Opt Eng. 1996;35:376–83.

    Google Scholar 

  21. Moss JP, Grindrod SR, Linney AD, Arridge SR, James D. A computer system for the interactive planning and prediction of maxillofacial surgery. Am J Orthod Dentofac Orthop. 1988;94:469–75.

    CAS  Google Scholar 

  22. Bajaj-Luthra A, Mueller T, Johnson P Quantitative analysis of facial motion components: anatomic and nonanatomic motion in normal persons and in patients with complete facial paralysis. Plast Reconstr Surg.1997;99:1894–1902. discussion 903e4.

    Google Scholar 

  23. Ferrario VF, Sforza C, Poggio CE, Tartaglia G. Distance from symmetry: a three-dimensional evaluation of facial asymmetry. J Oral Maxillofac Surg. 1994;52:1126–32.

    CAS  PubMed  Google Scholar 

  24. Trotman C, Gross M, Moffatt K. Reliability of a threedimensional method for measuring facial animation: a case report. Angle Orthod. 1996;66:195–8.

    CAS  PubMed  Google Scholar 

  25. Frey M, Giovanoli P, Gerber H, Slameczka M, Stu¨ssi E. Threedimensional video analysis of facial movements: a new method to assess the quantity and quality of the smile. Plast Reconstr Surg. 1999;104:2032–9.

    CAS  PubMed  Google Scholar 

  26. Olesen OV, Paulsen RR, Hojgaar L, Roed B, Larsen R. Motion tracking in narrow spaces: a structured light approach. Med Image Comput Comput Assist Interv. 2010;13:253–60.

    PubMed  Google Scholar 

  27. Edge JD, Hilton A, Jackson P. Model-based synthesis of visual speech movements from 3D video. EURASIP J Audio Speech Music Process. 2009;2009:12.

    Google Scholar 

  28. Lane C, Harrell W Jr. Completing the 3-dimensional picture. Am J Orthod Dentofac Orthop. 2008;133:612–20.

    Google Scholar 

  29. Tian GY, Lu RS, Gledhill D. Surface measurement using active vision and light scattering. Opt Laser Eng. 2007;45:131–9.

    Google Scholar 

  30. Li W, Li YF. Single-camera panoramic stereo imaging system with a fisheye lens and a convex mirror. Opt Express. 2011;19:5855–67.

    PubMed  Google Scholar 

  31. Wei GQ, Dema S. Implicit and explicit camera calibration—theory and experiments. IEEE Trans Pattern Anal Mach Intell. 1994;16:469–80.

    Google Scholar 

  32. Tzou C-HJ, et al. Comparison of three-dimensional surface-imaging systems. J Plast Reconstr Aesthet Surg. 2014;67:489–97.

    PubMed  Google Scholar 

  33. Camison L, et al. Validation of the Vectra H1 portable three-dimensional photogrammetry system for facial imaging. Int J Oral Maxillofac Surg. 2018;47:403–10.

    CAS  PubMed  Google Scholar 

  34. Aldridge K, Boyadjiev SA, Capone GT, DeLeon VB, Richtsmeier JT. Precision and error of three-dimensional phenotypic measures acquired from 3dMD photogrammetric images. Am J Med Genet Part A. 2005;138A:247–53.

    PubMed  Google Scholar 

  35. Weinberg SM, Naidoo S, Govier DP, Martin RA, Kane AA, Marazita ML. Anthropomet- ric precision and accuracy of digital threedimensional photogrammetry: comparing the Genex and 3dMD imaging systems to one another and to direct anthropometry. J Craniofac Surg. 2006;17:477–83.

    PubMed  Google Scholar 

  36. Wong JY, Oh AK, Ohta E, Hunt AT, Rogers GF, Mulliken JB, Deutsch CK. Validity and reliability of craniofacial anthropometric measurement of 3D digital photogrammetric images. Cleft Palate Craniofac J. 2008;45:232–9.

    PubMed  Google Scholar 

  37. Heike CL, Cunningham ML, Hing AV, Stuhaug E, Starr JR. Picture perfect? Reliability of craniofacial anthropometry using threedimensional digital stereophotogrammetry. Plast Reconstr Surg. 2009;124:1261–72.

    CAS  PubMed  Google Scholar 

  38. https://www.aniwaa.com/product/3d-scanners/3dmd-3dmdface-system/.

  39. Schendel SA, Montgomery K. A web-based, integrated simulation system for craniofacial surgical planning. Plast Reconstr Surg. 2009;123:1099–106.

    CAS  PubMed  Google Scholar 

  40. http://www.dirdim.com/pdfs/DDI_Dimensional_Imaging_DI3D.pdf.

  41. Gibelli D, Pucciarelli V, Cappella A, Dolci C, Sforza C. Are portable stereo photogrammetric devices reliable in facial imaging? A validation study of VECTRA H1 device. J Oral Maxillofac Surg. 2018;76:1772–84.

    PubMed  Google Scholar 

  42. Lee KC, Dretzke J, Grover L, Logan A, Moiemen N. A systematic review of objective burn scar measurements. Burns Trauma. 2016;4:14.

    PubMed  PubMed Central  Google Scholar 

  43. Mitsuno D, Ueda K, Itamiya T, Nuri T, Otsuki Y. Intraoperative evaluation of body surface improvement by an augmented reality system that a clinician can modify: Plast. Reconstr Surg Glob Open. 2017;5:e1432.

    Google Scholar 

  44. Schreiber JE, et al. The boomerang lift: A three-step compartment-based approach to the youthful cheek. Plast Reconstr Surg. 2018;141:910–3.

    CAS  PubMed  Google Scholar 

  45. Milani M, Sparavigna A. Antiaging efficacy of melatonin-based day and night creams: a randomized, split-face, assessor-blinded proof-of-concept trial. Clin Cosmet Investig Dermatol. 2018;11:51–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Urbanová P, Hejna P, Jurda M. Testing photogrammetry-based techniques for three-dimensional surface documentation in forensic pathology. Forensic Sci Int. 2015;250:77–86.

    PubMed  Google Scholar 

  47. O’Connell RL, et al. Validation of the Vectra XT three-dimensional imaging system for measuring breast volume and symmetry following oncological reconstruction. Breast Cancer Res Treat. 2018;171:391–8.

    PubMed  PubMed Central  Google Scholar 

  48. Oliveira-Santos T, et al. 3D face reconstruction from 2D pictures: First results of a web-based computer aided system for aesthetic procedures. Ann Biomed Eng. 2013;41:952–66.

    PubMed  Google Scholar 

  49. Petit L, et al. Validation of 3D skin imaging for objective repeatable quantification of severity of atrophic acne scarring. Skin Res Technol. 2018;24:542–50.

    CAS  PubMed  Google Scholar 

  50. Brauer JA, et al. Use of a picosecond pulse duration laser with specialized optic for treatment of facial acne scarring. JAMA Dermatol. 2015;151:278.

    PubMed  Google Scholar 

  51. http://www.cmconsulenze.it/antera_3d_analisi_cutanea.php.

  52. Linming F, et al. Comparison of two skin imaging analysis instruments: The VISIA ® from Canfield vs the ANTERA 3D ® CS from Miravex. Skin Res Technol. 2018;24:3–8.

    CAS  PubMed  Google Scholar 

  53. Goldsberry A, Hanke CW, Hanke KE. VISIA system: a possible tool in the cosmetic practice. J Drugs Dermatol JDD. 2014;13(11):1312–4.

    PubMed  Google Scholar 

  54. Cygler K. VISIA complexion analysis med spa. Recorded Nov 5, 2013. http://www1.gotomeeting.com/register/783169248. Accessed 16 May 2014

  55. Demirli R, Otto P, Viswanathan R, Patwardhan S, Larkey J RBX® technology overview. 1701–13. http://www.canfieldsci.com/FileLibrary/RBX%20tech%20overview-LoRz1.pdf.

  56. https://www.canfieldsci.com/imaging-systems/reveal-imager/.

  57. Rayner JE, et al. Clinical perspective of 3D total body photography for early detection and screening of melanoma. Front Med. 2018;5.

    Google Scholar 

  58. Hibler B, Qi Q, Rossi A. Current state of imaging in dermatology. Semin Cutan Med Surg. 2016;35:2–8.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Campana, I., Tonini, G., Perrot, J.L., Cinotti, E. (2020). 3D Imaging. In: Fimiani, M., Rubegni, P., Cinotti, E. (eds) Technology in Practical Dermatology. Springer, Cham. https://doi.org/10.1007/978-3-030-45351-0_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-45351-0_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45350-3

  • Online ISBN: 978-3-030-45351-0

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics