Enhanced Visualisation of Normal Anatomy with Potential Use of Augmented Reality Superimposed on Three-Dimensional Printed Models.
Jade Geerlings-BattCarley TillettAshu GuptaZhonghua SunPublished in: Micromachines (2022)
Anatomical knowledge underpins the practice of many healthcare professions. While cadaveric specimens are generally used to demonstrate realistic anatomy, high cost, ethical considerations and limited accessibility can often impede their suitability for use as teaching tools. This study aimed to develop an alternative to traditional teaching methods; a novel teaching tool using augmented reality (AR) and three-dimensional (3D) printed models to accurately demonstrate normal ankle and foot anatomy. An open-source software (3D Slicer) was used to segment a high-resolution magnetic resonance imaging (MRI) dataset of a healthy volunteer ankle and produce virtual bone and musculature objects. Bone and musculature were segmented using seed-planting and interpolation functions, respectively. Virtual models were imported into Unity 3D, which was used to develop user interface and achieve interactability prior to export to the Microsoft HoloLens 2. Three life-size models of bony anatomy were printed in yellow polylactic acid and thermoplastic polyurethane, with another model printed in white Visijet SL Flex with a supporting base attached to its plantar aspect. Interactive user interface with functional toggle switches was developed. Object recognition did not function as intended, with adequate tracking and AR superimposition not achieved. The models accurately demonstrate bony foot and ankle anatomy in relation to the associated musculature. Although segmentation outcomes were sufficient, the process was highly time consuming, with effective object recognition tools relatively inaccessible. This may limit the reproducibility of augmented reality learning tools on a larger scale. Research is required to determine the extent to which this tool accurately demonstrates anatomy and ascertain whether use of this tool improves learning outcomes and is effective for teaching anatomy.
Keyphrases
- healthcare
- magnetic resonance imaging
- high resolution
- medical students
- virtual reality
- contrast enhanced
- computed tomography
- machine learning
- type diabetes
- magnetic resonance
- climate change
- metabolic syndrome
- adipose tissue
- convolutional neural network
- soft tissue
- insulin resistance
- skeletal muscle
- quality improvement
- ultrasound guided
- human health