Comparison of medical image 3D reconstruction rendering methods for robot-assisted surgery

Abstract

In modern medicine, 3D reconstruction plays an important role in improving the accuracy of disease detection and treatment especially in the process of robot-assisted surgery. Accordingly, the choice of 3D reconstruction method is of great importance, which provides real-time visualization. This study analyses and compares two types of methods in 3D medical image reconstruction and visualization: Surface Rendering and Volume Rendering. To be more specific, four algorithms including Contour Filter (CF), Marching Cubes (MC), Composite Volume Rendering (CVR) and Texture Mapping Hardware (TMH) were implemented and compared from the perspective of the rendering effect, speed and interactivity, in which the former two algorithms belong to the concept of Surface Rendering and the latter two algorithms are in the range of Volume Rendering. These algorithms were implemented by Microsoft Visual Studio with Visualization Toolkit (VTK) to reconstruct the 3D images of patients CT image data. The mechanism and realization of these algorithms were described, and the merits and shortcomings of these different rendering methods were compared. Based on the comparison results, the 3D reconstruction and rendering method can be determined according to the specific requirements of robot-assisted surgery.