The potential of 3D models and augmented reality in teaching cross-sectional radiology.
3D segmentation
anatomic structures
augmented reality
medical education
medical imaging
Journal
Medical teacher
ISSN: 1466-187X
Titre abrégé: Med Teach
Pays: England
ID NLM: 7909593
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
medline:
26
9
2023
pubmed:
5
8
2023
entrez:
4
8
2023
Statut:
ppublish
Résumé
What was the educational challenge?The complexity and variability of cross-sectional imaging present a significant challenge in imparting knowledge of radiologic anatomy to medical students.What was the solution?Recent advancements in three-dimensional (3D) segmentation and augmented reality (AR) technology provide a promising solution. These advances allow for the creation of interactive, patient-specific 3D/AR models which incorporate multiple imaging modalities including MRI, CT, and 3D rotational angiography can help trainees understand cross-sectional imaging.How was the solution implemented?To create the model, DICOM files of patient scans with slice thicknesses of 1 mm or less are exported to a computer and imported to 3D Slicer for registration. Once registered, the files are segmented with Vitrea software utilizing thresholding, region growing, and edge detection. After the creation of the models, they are then imported to a web-based interactive viewing platform and/or AR application.What lessons were learned that are relevant to a wider global audience?Low-resource 3D/AR models offer an accessible and intuitive tool to teach radiologic anatomy and pathology. Our novel method of creating these models leverages recent advances in 3D/AR technology to create a better experience than traditional high and low-resource 3D/AR modeling techniques. This will allow trainees to better understand cross-sectional imaging.What are the next steps?The interactive and intuitive nature of 3D and AR models has the potential to significantly improve the teaching and presentation of radiologic anatomy and pathology to a medical student audience. We encourage educators to incorporate 3D segmentation models and AR in their teaching strategies.
Identifiants
pubmed: 37542360
doi: 10.1080/0142159X.2023.2242170
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM