Summary: Tomography means reconstructing the internal structure of a physical object using the X-ray images of the object taken from different directions. Mathematically, the problem is to recover a non-negative function f(x) from a collection of the line integrals of f. Here we show how to solve a dynamic tomography ( continue reading… )
Summary: Tomography means reconstructing the internal structure of a physical body using X-ray images of the body taken from different directions. Mathematically, the problem is to recover a non-negative function f(x) from a collection of line integrals of f. Here we show how to solve the tomography problem using Total ( continue reading… )
Summary: Tomography means reconstructing the internal structure of a physical body using X-ray images of the body taken from different directions. Mathematically, the problem is to recover a non-negative function f(x) from a collection of line integrals of f. Here we show how to solve the tomography problem using Total Variation ( continue reading… )
Summary: Choosing the regularization parameter is a hard problem, for which many approaches exist. Here we discuss the recently developed and fully automatic method, called controlled wavelet domain sparsity (CWDS) in the context of X-ray tomography. This approach involves sparsity promoting regularization with respect to an orthogonal wavelet basis. The ( continue reading… )
Summary: Tomography means reconstructing the internal structure of a physical body using X-ray images of the body taken from different directions. Mathematically, the problem is to recover a non-negative function f(x) from a collection of line integrals of f. Here we show how to solve the tomography problem using Total ( continue reading… )
Summary: Tomography means reconstructing the internal structure of a physical body using X-ray images of the body taken from different directions. Mathematically, the problem is to recover a non-negative function f(x) from a collection of line integrals of f. Here we show how to solve the tomography problem using truncated ( continue reading… )