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The proper analysis of biological microscopy images is an important and complex task. Therefore, it requires verification of all steps involved in the process, including image segmentation and tracking algorithms. It is generally better to verify algorithms with computer-generated ground truth datasets, which, compared to manually annotated data, nowadays have reached high quality and can be produced...
In fluorescence microscopy, where the benchmark datasets for validating the various image analysis methods are difficult to obtain, a great demand is either for manually annotated real image data or for realistic computer generated ones. In the last two decades, the latter case has become more and more accessible due to an increasing computer capabilities. However, the development of elaborate models,...
The recognition of patterns with focus on texture and shape analysis is still very hot topic, especially in biomédical image processing. In this article, we introduce 3D extensions of well-known approaches for this particular area. We focus on the collection of MPEG-7 image descriptors, specifically on the Edge Histogram Descriptor (EHD) and Gabor features, which are the core of the Homogeneous Texture...
In biomedical image analysis, object description and classification tasks are very common. Our work relates to the problem of classification of Human Epithelial (HEp-2) cells. Since the crucial part of each classification process is the feature extraction and selection, much attention should be concentrated to the development of proper image descriptors. In this article, we introduce a new efficient...
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