Image reconstruction techniques applied to nuclear mass models

Image reconstruction techniques applied to nuclear mass models

Irving O. Morales,1 P. Van Isacker,2 V. Velazquez,3 J. Barea,4 J. Mendoza-Temis,1 J. C. López Vieyra,1 J. G. Hirsch,1 and A. Frank1 1Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, 04510 México, D.F., Mexico 2Grand Accélérateur National d’Ions Lourds, CEA/DSM–CNRS/IN2P3, Boı̂te Postale 55027, F-14076 Caen Cedex 5, France 3Facultad de Ciencias, Universidad Nacional Autón...

Image Reconstruction Techniques

Image reconstruction in CT is a mathematical process that generates tomographic images from X-ray projection data acquired at many different angles around the patient. Image reconstruction has fundamental impacts on image quality and therefore on radiation dose. For a given radiation dose it is desirable to reconstruct images with the lowest possible noise without sacrificing image accuracy and...

Image Reconstruction Techniques for PET

Nonlinear Optimal Control Techniques Applied to a Launch Vehicle Autopilot

This paper presents an application of the nonlinear optimal control techniques to the design of launch vehicle autopilots. The optimal control is given by the solution to the Hamilton-Jacobi-Bellman (HJB) equation, which in this case cannot be solved explicity. A method based upon Successive Galerkin Approximation (SGA), is used to obtain an approximate optimal solution. Simulation results invo...

Partial Differential Equations applied to Medical Image ‎Segmentation

‎This paper presents an application of partial differential equations(PDEs) for the segmentation of abdominal and thoracic aortic in CTA datasets. An important challenge in reliably detecting aortic is the need to overcome problems associated with intensity inhomogeneities. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been exte...