Three Dimensional Reconstruction of Human Heart Surface from Single Image-View Under Different Illumination Conditions

Abstract

The 3D reconstruction from a single-view image is a longstanding issue in computer vision literature, especially in the medical field. Traditional medical imaging techniques that provide information about the heart and which are used to reconstruct the heart model, include Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images. However, in some cases, they are not available and the applications that use these techniques to model the human heart only produce acceptable results after a long process, which involves acquiring the input data, as well as the segmentation process, the matching process, effort and cost. Therefore, it would be useful to be able to use a 2D single image to reconstruct the 3D heart surface model. We introduce an image-based human heart surface reconstruction from a single image as input. To model the surface of the heart, the proposed method, first, detects and corrects the specular reflection from the heart’s surface, which causes deformation of the surface in the R3. Second, it extrudes the three axes for each image pixel (e.g., x, y and z axes) from the input image, in which the z-axis is calculated using the intensity value. Finally, a 3D reconstruction of the heart surface is created to help the novice cardiac surgeon to reduce the period of time in learning cardiac surgery and to enhance their perception of the operating theatre. The experimental results for images of the heart show the efficiency of the proposed method compared to the existing methods.