Pawel Szwarc

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The paper deals with the segmentation of brain tumours in Magnetic Resonance (MR) images. The segmentation method developed is based on the analysis of three MR series namely: T1-weighted (T1W), contrast enhanced T1W (CE-T1W) and perfusion maps images. The differential images after and before contrast agent administration are segmented with the use of the(More)
In this paper a novel multi-stage automatic method for brain tumour detection and neovasculature assessment is presented. First, the brain symmetry is exploited to register the magnetic resonance (MR) series analysed. Then, the intracranial structures are found and the region of interest (ROI) is constrained within them to tumour and peritumoural areas(More)
The paper presents a Computer Aided Diagnosis (CAD) software for brain tumor detection and analysis from Magnetic Resonance Imaging (MRI). The software utilizes a novel multi-stage method that is capable of dealing with three main types of brain tumors, i.e. HG gliomas, metastases and meningiomas and yields object masks as well as quantitative parameters.(More)
This paper presents research on automatic spoken language recognition based on statistical pattern recognition. As a model of identified language Gaussian Mixture Model was applied, both with diagonal and full covariance matrix. The influence of GMM order and parameterizations of speech signal on the recognition results were examined. Tests were done for 10(More)
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