Eva Gescheidtova

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Imaging techniques based on the principles of nuclear magnetic resonance (NMR) are modern techniques for the study of chemical, biological and physical properties of substances. The most important are their applications in medical sciences. MR imaging of a specimen weighted with diffusion coefficients requires very accurate data on the time course of the(More)
The subject of the paper is a method proposed for automated evaluation of the parameters of orthopantomograms of cystic disorders in human jawbones. The main problem in medical diagnostic is the low repeatability due to the subjective evaluation of images/pictures without using a tool for image processing. An available database of images of cysts is(More)
The problem most frequently encountered in the practical processing of medical images consists in the lack of instruments enabling machine evaluation of the images. A typical example of this situation is perfusion analysis of brain tumor types. The first and very significant step lies in the segmentation of individual parts of the brain tumor; after(More)
Removing noise from an free induction decay (FID) signal is of fundamental significance in the analysis of results of magnetic resonance (MR) spectroscopy and tomography. Optimum solution can be seen in removing noise by means of a digital filter bank that uses half-band mirror frequency filters of the type of low-pass and high-pass filters. A filtering(More)
The application of a DSP96002 digital signal processor in measuring and transferring data, setting the preemphasis constants, and communicating with the MR tomograph is described in the paper. The application of the digital signal processor represents a modern approach to real-time processing of MR signals. The objective is to obtain distance communication(More)
The authors present a statistical evaluation of T<sub>1</sub>-weighted and T<sub>2</sub>-weighted images of healthy and diseased human tissues. In each patient, the statistical data were evaluated from several tissues, namely the bone, bone marrow, muscle, fat, white matter and gray matter tissue types. Based on the acquired statistical data, we compiled(More)