Evaluation of a fully automatic medical image registration algorithm based on mutual information

Registration is a fundamental task in image processing. Its purpose is to find a geometrical transformation that relates the points of an image to their corresponding points of another image. Many registration algorithms have been proposed in the past decade. We present a fast, fully automatic algorithm that is capable of solving rigid-body registration of 3D images of the human brain where the images are taken by different imaging devices. We joined the Retrospective Registration Evaluation Project conducted by Vanderbilt University, USA. The evaluations of our results show that our method has the potential to produce satisfactory results, but visual inspection is necessary to guard against large errors

Reconstruction of binary matrices from fan-beam projections

The problem of the reconstruction of binary matrices from their fan-beam projections is investigated here. A fan-beam projection model is implemented and afterwards employed in systematic experiments to determine the optimal parameter values for a data acquisition and reconstruction algorithm. The fan-beam model, the reconstruction algorithm which uses the optimization method of Simulated Annealing, the simulation experiments, and the results are then discussed in turn

Affine matching of two sets of points in arbitrary dimensions

In many applications of computer vision, image processing, and remotely sensed data processing, an appropriate matching of two sets of points is required. Our approach assumes one-to-one correspondence between these sets and finds the optimal global affine transformation that matches them. The suggested method can be used in arbitrary dimensions. A sufficient existence condition for a unique transformation is given and proven

Image reconstruction and correction methods in neutron and X-ray tomography

Neutron and X-ray tomography are imaging techniques for getting information about the interior of objects in a non-destructive way. They reconstruct cross-sections from projection images of the object being investigated. Due to the properties of the image acquisition system, the projection images are distorted by several artifacts, and these reduce the quality of the reconstruction. In order to eliminate these harmful effects the projection images should be corrected before reconstruction. Taking projections is usually an expensive and time consuming procedure. One of our main goals has been to try to minimize the number of projections - for example, by exploiting more a priori information. A possible way of reducing the number of projections is by the application of discrete tomographic methods. In this case a special class of objects can be reconstructed, consisting of only a few homogenous materials that can be characterized by known discrete absorption values. To this end we have implemented two reconstruction methods. One is able to reconstruct objects consisting of cylinders and spheres made of homogeneous materials only. The other method is a general one in the sense that it can be used for reconstructing any shape. Simulations on phantoms and physical measurements were carried out and the results are presented here

Parameter Settings for Reconstructing Binary Matrices from Fan-Beam Projections

The problem of reconstruction of binary matrices from their fan-beam projections is studied. A fan-beam projection model is implemented and used in systematic experiments in order to determine the optimal parameter values for data acquisition and reconstruction algorithm. The fan-beam model, the reconstruction algorithm, the simulation experiments, and the results are discussed in the paper