2D to 3D Conversion of Images Using Defocus Method Along with Laplacian Matting for Improved Medical Diagnosis

In today’s medicine field, there is an increasing need to be more efficient and to be able to develop new techniques to diagnose and cure different diseases and ailments. From the wide range of medical images, there has been an initiative to concentrate or restrict the implementation to X-rays, since X-ray images are the only valid analogies that can be compared to vision from a camera with a perspective. Due to the older diagnosis methods implemented, there is an excess of 2D data when compared to 3D data. Therefore, conversion of 2D data to 3D plays an important factor in arriving at the required result with higher efficiency since it is more cost effective to convert 2D images to 3D rather than create a 3D image from scratch. In this work, the first concept used is of defocus method to perform the depth estimation of the given X-ray image, with the help of edge detection and the second concept used is, gradient magnitude calculation along with image matting using Laplacian process to produce a 3D structure of the 2D image.