New Method for 4D Reconstruction of Medical Images

This paper proposes a new optimized method that is fast in rendering for 4D reconstruction from 2D medical images of human anatomy permitting their real-time refined visualization. This method uses the 3D reconstruction algorithm based on contour matching of medical image sequences and on the tessellation of recent GPU. In our framework, the construction of the low-resolution mesh that is based on contour extraction allows to create a 3D mesh without any ambiguity and exactly matches the real shape of the human anatomy. Such preliminary result is of great interest, since it permits to lead to other valuable realizations such as reducing the computation burden of basic meshes and displacement vectors. Moreover, one can achieve a very low storage memory, as well as one can ease the fast real-time 4D visualization with a high desired resolution. Hence, it is then straight forward that this study can contribute to easing the diagnosis and detection in real-time of human organs in motion damage and deterioration. Especially, 4D visualization technology that is still under development is highly important and needed for assessing some dangerously evaluative diseases, as in the case of lung diseases.