Search for: All records

In the past decade, the ability to construct digital models of natural history specimens has become faster, cheaper, and easier for researchers. This in part has led to the modern movement to cre- ate models of representatives of all vertebrate species and make these data freely available to other researchers and the general public. The openVertebrate project (or “oVert”) is leading this charge by using micro computed tomographic (μCT) scanners at universities across the United States to synchronously tackle this ambitious initiative. But what happens to a specimen in a museum before a digital model of that specimen is published on the internet? Here we provide a window into some of the steps involved in this process and focus on what is involved in scanning specimens of fishes. 

The decreasing cost of acquiring computed tomographic (CT) data has fueled a global effort to digitize the anatomy of museum specimens. This effort has produced a wealth of open access digital 3D models of anatomy available to anyone with access to the internet. The potential applications of these data are broad, ranging from 3D printing for purely educational purposes to the development of highly advanced biomechanical models of anatomical structures. However, while virtually anyone can access these digital data, relatively few have the training to easily derive a desirable product (e.g., a 3D visualization of an anatomical structure) from them. Here, we present a workflow based on free, open source, cross-platform software for processing CT data. We provide step-by-step instructions that start with acquiring CT data from a new reconstruction or an open access repository, and progress through visualizing, measuring, landmarking, and constructing digital 3D models of anatomical structures. We also include instructions for digital dissection, data reduction, and exporting data for use in downstream applications such as 3D printing. Finally, we provide supplementary videos and workflows that demonstrate how the workflow facilitates five specific applications: measuring functional traits associated with feeding, digitally isolating anatomical structures, isolating regions of interest using semi-automated segmentation, collecting data with simple visual tools, and reducing file size and converting file type of a 3D model.