Details

Autor(en) / Beteiligte

• Oliveira, André S. B.
• Leonel, Luciano C. P. C.
• Bauman, Megan M. J.
• De Bonis, Alessandro
• LaHood, Edward R.
• Graepel, Stephen
• Link, Michael J.
• Pinheiro-Neto, Carlos D.
• Lachman, Nirusha
• Morris, Jonathan M.
• Peris-Celda, Maria

Titel

Photogrammetry scans for neuroanatomy education - a new multi-camera system: technical note

Ist Teil von

• Neuroinformatics (Totowa, N.J.), 2024-07, Vol.22 (3), p.317-327

Ort / Verlag

New York: Springer US

Erscheinungsjahr

2024

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Photogrammetry scans has directed attention to the development of advanced camera systems to improve the creation of three-dimensional (3D) models, especially for educational and medical-related purposes. This could be a potential cost-effective method for neuroanatomy education, especially when access to laboratory-based learning is limited. The aim of this study was to describe a new photogrammetry system based on a 5 Digital Single-Lens Reflex (DSLR) cameras setup to optimize accuracy of neuroanatomical 3D models. One formalin-fixed brain and specimen and one dry skull were used for dissections and scanning using the photogrammetry technique. After each dissection, the specimens were placed inside a new MedCreator® scanner (MedReality, Thyng, Chicago, IL) to be scanned with the final 3D model being displayed on SketchFab® (Epic, Cary, NC) and MedReality® platforms. The scanner consisted of 5 cameras arranged vertically facing the specimen, which was positioned on a platform in the center of the scanner. The new multi-camera system contains automated software packages, which allowed for quick rendering and creation of a high-quality 3D models. Following uploading the 3D models to the SketchFab® and MedReality® platforms for display, the models can be freely manipulated in various angles and magnifications in any devices free of charge for users. Therefore, photogrammetry scans with this new multi-camera system have the potential to enhance the accuracy and resolution of the 3D models, along with shortening creation time of the models. This system can serve as an important tool to optimize neuroanatomy education and ultimately, improve patient outcomes.