Tomographic reconstruction of an object’s interior volume from limited angular views is a challenging problem with practical applications in biological imaging, failure analysis of integrated circuits, etc. A team at MIT presents a dynamical machine learning approach for this important problem and shows the method’s performance in two problems—tomography under weak and strong scattering conditions. The wide applicability of this technique holds its promise for a number of other challenging inverse problems.
Click here for original story, Dynamical machine learning accurately reconstructs volume interiors with limited-angle data
Source: Phys.org