Which Tool Is Best: 3D Scanning or Photogrammetry – It Depends on the Task

  • Ishan Dixit
  • Samantha Kennedy
  • Joshua Piemontesi
  • Bruce Kennedy
  • Claudia KrebsEmail author
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1120)


In many educational and clinical settings we are increasingly looking into methodologies for accurate 3D representations of structures and specimens. This is relevant for anatomy teaching, pathology, forensic and anthropological sciences, and various clinical fields. The question then arises which tool best suits the task at hand – both 3D scanning and photogrammetry are options. For the use in medical education the aim is to create 3D models of anatomical specimens with high quality and resolution. Various qualitative and quantitative criteria determine the performance fidelity and results of 3D scanning versus photogrammetry. In our work we found that photogrammetry provides more realistic surface textures and very good geometries for most specimens. 3D surface scanning captures more accurate geometries of complex specimens and in specimens with reflective surfaces. The 3D scanning workflow and capture method is more practical for soft specimens where movement of the sample can lead to distortions. Overall, both methods are highly recommended dependent on the nature of the specimen and the use case of the 3D model.


Medical education Anatomy Photogrammetry 3D scanning 3D learning Digitization 


  1. Azer SA, Azer S (2016) 3D anatomy models and impact on learning: a review of the quality of the literature. Health Prof Educ 2:80–98. CrossRefGoogle Scholar
  2. Boehler W, Marbs A (2004) 3D scanning and photogrammetry for heritage recording: a comparison. In: Proceedings of the 12th International conference on geoinformatics, University of Gävle, Sweden 7–9Google Scholar
  3. Brazina D, Fojtik R, Rombova Z (2014) 3D visualization in teaching anatomy. Procedia Soc Behav Sci 143:367–371. CrossRefGoogle Scholar
  4. Camba JD, Contero M (2015) From reality to augmented reality: rapid strategies for developing marker-based AR content using image capturing and authoring tools. In: 2015 IEEE frontiers in education conference.
  5. Evin A, Souter T, Hulme-Beaman A et al (2016) The use of close-range photogrammetry in zooarchaeology: creating accurate 3D models of wolf crania to study dog domestication. J Archaeol Sci Rep 9:87–93. CrossRefGoogle Scholar
  6. Foster S, Halbstein D (2014) Integrating 3D modeling, photogrammetry and design, SpringerBriefs in Computer Science. Springer, LondonCrossRefGoogle Scholar
  7. Incekara AH, Seker DZ (2018) Comparative analyses of the point cloud produced by using close-range photogrammetry and terrestrial laser scanning for rock surface. J Indian Soc Remote Sens 46:1243–1253CrossRefGoogle Scholar
  8. Jebur A, Abed F, Mohammed M (2018) Assessing the performance of commercial Agisoft PhotoScan software to deliver reliable data for accurate3D modelling. MATEC Web Conf 162.
  9. Katz D, Friess M (2014) Technical note: 3D from standard digital photography of human crania – a preliminary assessment. Am J Phys Anthropol 154:152–158. CrossRefPubMedGoogle Scholar
  10. Knibbe J, O'Hara K (2014) Quick and dirty: streamlines 3D scanning in archeology. In: Proceedings of the 17th ACM conference on computer supported cooperative work & social computing, pp 1366–1376.
  11. Linder W (2016) Introduction BT – digital photogrammetry: a practical course. Springer, Berlin/HeidelbergGoogle Scholar
  12. Saltarelli AJ, Roseth CJ, Saltarelli WA (2014) Human cadavers vs. multimedia simulation: A study of student learning in anatomy. Anat Sci Educ 7:331–339. CrossRefPubMedGoogle Scholar
  13. Sapirstein P (2018) A high-precision photogrammetric recording system for small artifacts. J Cult Herit 31:33–45CrossRefGoogle Scholar
  14. Tam MDBS (2010) Building virtual models by postprocessing radiology images: a guide for anatomy faculty. Anat Sci Educ 3:261–266. CrossRefPubMedGoogle Scholar
  15. Viggiano D, Thanassoulas T, Di-Cesare C et al (2015) A low-cost system to acquire 3D surface data from anatomical samples. Eur J Anat 19:343–349Google Scholar
  16. Westoby MJ, Brasington J, Glasser NF et al (2012) “Structure-from-motion” photogrammetry: a low-cost, effective tool for geoscience applications. Geomorphology 179:300–314. CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ishan Dixit
    • 1
  • Samantha Kennedy
    • 2
  • Joshua Piemontesi
    • 2
  • Bruce Kennedy
    • 3
  • Claudia Krebs
    • 4
    Email author
  1. 1.School of Kinesiology, Faculty of EducationUniversity of British ColumbiaVancouverCanada
  2. 2.Medical Undergraduate Program, Island Medical ProgramUniversity of British ColumbiaVancouverCanada
  3. 3.Victoria Police Forensic Identification Specialist (retired)VictoriaCanada
  4. 4.Department of Cellular and Physiological SciencesUniversity of British ColumbiaVancouverCanada

Personalised recommendations