Abstract
Introduction: Virtual three-dimensional (3D) anatomical models can improve diagnostic and surgical medical procedures with a patient-specific approach. The advantage of these models, in opposition to CT scans or MRIs alone, is their unique ability to demonstrate anatomical spatial relationship with submillimetre accuracy. Methods: Starting from our platform Med3D VR Lab, we implemented, in the MMM project, a basic algorithm within a software, able to capture, from DICOM images (MRIs/CT scans), the cloud of points needed to build 3D images. Different areas of a tissue might have different radio-density levels. In these cases, we applied our patented algorithm to harmonize these values through a transformation matrix. Results: We created a VR Laboratory (via a supervised learned approach) to access the resulting 3D image. The user, by wearing a VR headset, can rotate and enlarge the heart’s model. By cutting the model with the scalpel tool, the user is able to see the interior of the 3D model. The sections of the heart are created according to the direction of the cut. Each section can be further cut into smaller sub-sections, and both sections and sub-sections can be saved for future use. Conclusions: We developed a software for the conversion of 2D cardiac images in 3D models, which can be further examined and sectioned in a VR environment. This technique could help cardiologists in refining diagnosis and surgeons in tailoring cardiac interventions on the basis of patients’ characteristics, thus reducing operating times and costs while also preventing possible complications in cardiac surgery- therefore allowing to precisely assess risks in advance. Moreover, our software, through the VR visor, allows patients to truly understand their clinical conditions, thus overcoming the drawbacks of expressing an informed consent based only on DICOM imaging: the patients themselves will be able to understand the risks and benefits of a given surgical operations or its alternatives.
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