Measuring the motion of the small foot bones is critical for understanding pathological loss of function. Biplanar videoradiography is well-suited to measure in vivo bone motion, but challenges arise when estimating the rotation and translation (pose) of each bone. The bone's pose is typically estimated with marker-or model-based methods. Marker-based methods are highly accurate but uncommon in vivo due to their invasiveness. Model-based methods are more common but are currently less accurate as they rely on user input and lab-specific algorithms. This work presents a rare in vivo dataset of the calcaneus, talus, and tibia poses, as measured with marker-based methods during running and hopping. A method is included to train users to improve their initial guesses into model-based pose estimation software, using marker-based visual feedback. New operators were able to estimate bone poses within 2° of rotation and 1 mm of translation of the marker-based pose, similar to an expert user of the model-based software, and representing a substantial improvement over previously reported inter-operator variability. Further, this dataset can be used to validate other model-based pose estimation software. Ultimately, sharing this dataset will improve the speed and accuracy with which users can measure bone poses from biplanar videoradiography.

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The Insight Segmentation and Registration Toolkit (ITK) is a long-established, software package used for image analysis, visualization, and image-guided surgery applications. This package is a collection of C++ libraries, that can pose usability problems for users without C++ programming experience. To bridge the gap between the programming complexities and the required learning curve of ITK, we present a higher-level visual programming environment that represents ITK methods and classes by wrapping them into "blocks" within MATLAB's visual programming environment, Simulink. These blocks can be connected to form workflows: visual schematics that closely represent the structure of a C++ program. Due to the heavily C++ templated nature of ITK, direct interaction between Simulink and ITK requires an intermediary to convert their respective datatypes and allow intercommunication. We have developed a "Virtual Block" that serves as an intermediate wrapper around the ITK class and is responsible for resolving the templated datatypes used by ITK to native types used by Simulink. Presently, the wrapping procedure for SimITK is semi-automatic in that it requires XML descriptions of the ITK classes as a starting point, as this data is used to create all other necessary integration files. The generation of all source code and object code from the XML is done automatically by a CMake build script that yields Simulink blocks as the final result. An example 3D segmentation workflow using cranial-CT data as well as a 3D MR-to-CT registration workflow are presented as a proof-of-concept.

The Insight Segmentation and Registration Toolkit (ITK) is a software library used for image analysis, visualization, and image-guided surgery applications. ITK is a collection of C++ classes that poses the challenge of a steep learning curve should the user not have appropriate C++ programming experience. To remove the programming complexities and facilitate rapid prototyping, an implementation of ITK within a higher-level visual programming environment is presented: SimITK. ITK functionalities are automatically wrapped into "blocks" within Simulink, the visual programming environment of MATLAB, where these blocks can be connected to form workflows: visual schematics that closely represent the structure of a C++ program. The heavily templated C++ nature of ITK does not facilitate direct interaction between Simulink and ITK; an intermediary is required to convert respective data types and allow intercommunication. As such, a SimITK "Virtual Block" has been developed that serves as a wrapper around an ITK class which is capable of resolving the ITK data types to native Simulink data types. Part of the challenge surrounding this implementation involves automatically capturing and storing the pertinent class information that need to be refined from an initial state prior to being reflected within the final block representation. The primary result from the SimITK wrapping procedure is multiple Simulink block libraries. From these libraries, blocks are selected and interconnected to demonstrate two examples: a 3D segmentation workflow and a 3D multimodal registration workflow. Compared to their pure-code equivalents, the workflows highlight ITK usability through an alternative visual interpretation of the code that abstracts away potentially confusing technicalities.

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