Abstract
InVesalius is an open-source software for reconstruction of computed tomography and magnetic resonance images, which allows the user to make analysis and segmentation of virtual anatomical models. Physical models can be printed with the aid of rapid prototyping, giving the medical community a reliable instrument to help planning surgeries. To offer the user more control over the model, this work describes a methodology and tool developed for NURBS parameterization that provides mechanisms for adjusting the shape or even selecting a particular region of interest of the surface. Furthermore, the tool gives the option to export the final results of the process to a STEP file, which allows further edition in any well-known CAD software.
Highlights
Virtual modeling offers the clinical community the possibility to visualize the interior of the human body in a non-invasive way, allowing a more precise diagnosis of the patient
In order to generate an accurate model of the anatomical region to be studied, it is necessary to be able to work on medical images obtained from either computed tomography or magnetic resonance, such that one can correct many aspects susceptible to occur during acquisition, reconstruct and model the tridimensional surface by stacking bidimensional images, segment the surface into regions of interest, and acquire anatomical measurements, among other possible tasks
Since one of the goals of our work was to allow the user to reopen the surface generated by InVesalius in any Computer Aided Design (CAD) software, AP203 was chosen as the file type to export the reconstruction results
Summary
Virtual modeling offers the clinical community the possibility to visualize the interior of the human body in a non-invasive way, allowing a more precise diagnosis of the patient. In order to generate an accurate model of the anatomical region to be studied, it is necessary to be able to work on medical images obtained from either computed tomography or magnetic resonance, such that one can correct many aspects susceptible to occur during acquisition (e.g., equipment out of calibration or image artifacts caused by noise), reconstruct and model the tridimensional surface by stacking bidimensional images, segment the surface into regions of interest, and acquire anatomical measurements, among other possible tasks. In this context, the open-source software InVesalius [1] is a proper option to help in this entire process through its edition tools. Written mainly in Python programming language, the input data to InVesalius consist of medical image files, either in Digital Imaging and Communications in Medicine (DICOM) or in Analyze file formats, originated from computed tomography and magnetic resonance imaging. Many libraries are implemented to give support to the features offered by the software, such as wxPython for the graphical interface and Visualization Toolkit (VTK) [2] for 2D and 3D visualization of the images and surfaces
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