Intelligent Web-based Whole Body Visualization for Anatomy Education

Few subjects are as foundational to the practice of medicine as gross anatomy, yet few subjects are as resource-intensive to teach. The expense of cadavers, the high cost of maintaining lab spaces, and the increasing scarcity of the highly qualified expertise to teach the subject is driving the creation of software-based virtual methods of delivering instructional content to a willing population of technology-savvy students. There exists a collection of software-based solutions for anatomy instruction which have each contributed unique features facilitating the adoption of rich, digital learning environments. Biolucida [1], a 3D Virtual Realty based anatomy scene generator, takes another step toward promoting anatomy instruction in silico by allowing authors to create custom scenes and interactive lessons, including audio narration. Bioloucida also includes the ability to use intelligent queries to build scenes, with the assistance of the Foundational Model of Anatomy [2]. The FMA knowledgebase enables scene construction via queries such as “construct a scene from structures that are continuous with the aorta” rather than using a traditional line-item approach. While the functionality of Biolucida has allowed for the creation of novel interactive content, the system has suffered from an acute lack of 3D models. In this report, we describe a process of applying intelligent scene generation to a newly acquired complete set of 3D models representing the whole human body.