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3 Journal of Medical Informatics & Technologies

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Comparative investigations of similarity measure exploited in medical images preselection

Wróbel K., Porwik P.

Journal of Medical Informatics & Technologies

2004

Vol. 8

II25--31

Nowadays, the most significant impact of digital image processing in the area of applications are real–world problems. Many new technological trends in medicine and digital processing have been implemented. Several factors indicate such development. A major one is the perpetually declining cost of the computer equipment required. Both processing unit and capacity of storage devices continue to become less expensive year by year. Another factor is the increasing availability of equipment for digitising and displaying images. In modern image processing, images have to be compared each other because such approach allows us to automate of retrieval process. Computer image retrieving is today especially important in medical diagnostics [1,7] or in preliminary images selection [8,9]. Today, in the digital image processing are used techniques and methods which have well known mathematical backgrounds. It can be observed, that in the area of digital signal processing, the Hough and well known the Fourier transform are exploited very often. These transforms are frequently use in image retrieving and can be implemented as computer applications. In many cases the mentioned methods give promising results in images classification or preselection [1,2,4,5,11]. Special properties of such transforms can be used in statistical or comparative goals, especially when searched information has graphic form. Taking into account the mentioned applications, transforms as methods of preliminary medical images selection have been investigated. From this reason pictures, analysing in the paper, to medical images have been limited.

Automatic alignment of intramodal tomographic data using s-distance approach

Król Z.

Journal of Medical Informatics & Technologies

2003

Vol. 6

IT3--11

The alignment of volumetric datasets is an important problem in the processing of medical data. It is a prerequisite to numerous image based applications in diagnostic and therapeutic routines. In this paper, a new method is proposed for matching of 3D intramodality medical images. Our approach is based on some generalization of feature distance definition. Analogous to the standard surface matching, our algorithm uses also the chamfer distance like metric to define the quality of match function, however, the evaluation of the distance map is performed in a different way. The s-distance method is a step towards an automatic extraction of features, where each feature’s role in the registration process is weighted based on its relative statistical or spatial significance. As an alternative to the user-dependent non-automatic registration methods this approach offers a good assessment of similarity in the intramodality case. The elimination of less significant features in the registration process has resulted in a greatly improved efficiency over the voxel-based methods. Studying certain properties of the search space topography provides some insights into the performance of the proposed method as well as the standard registration algorithms in the rigid body registration problem.

Mutual information based registration of brain images

Kuczyński K., Mikołajczak P.

Journal of Medical Informatics & Technologies

2002

Vol. 3

MI213--219

Registration is one of the essential medical image processing techniques. The goal is to find a geometric transformation, that relates corresponding voxels in two different 3D images of the same object. The publication presents a registration technique based on maximization of mutual information.