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In this paper, a novel method for retina verification based on minutiae features is proposed. The method uses the vessel direction information for improved matching robustness, and is thus suitable for cases where the overlapping region of the matched images is limited. Verification achieves a low false rejection ratio (FRR) even when the retinal area overlap is as low as 25% of the total area. The...
Monitoring of bacterial populations requires automated analysis tools that provide accurate cell type quantification results. Here, methods for automated image analysis and bacteria type classification are presented. The classification method employs several discriminative features, calculated from automatically segmented images, for class determination. The performance of the algorithm is evaluated...
Subcellular organelles are commonly analyzed using 2D fluorescent microscopy. However, 3D reconstruction and analysis of organelle topology in a high-throughput manner promises to result in a better understanding of cellular systems. We developed image analysis methods for automated quantitative analysis of peroxisome shapes. The methods employ 3D image stacks obtained by confocal microscopy. There...
An automated image analysis method for identifying folds in tissue section images is presented. Tissue folding is a common artifact in histological images. Folding artifacts form when tissue folds over twice or more when placing it on the microscope slide. As analyzing cell nuclei automatically, the existence of these artifacts causes algorithms easily to give false output. Thus, their identification...
A segmentation method for three-dimensional image stacks obtained by confocal microscopy is proposed. The method can be used to find two-dimensional object areas based on an image stack. The segmentation method is based on K- means clustering, global thresholding, and mathematical morphology. As a case study, the proposed method is applied to 244 image stacks of the yeast Saccharomyces cerevisiae...
An automated image analysis method for extracting the number of peroxisomes in yeast cells is presented. Two images of the cell population are required for the method: a bright field microscope image from which the yeast cells are detected and the respective fluorescent image from which the number of peroxisomes in each cell is found. The segmentation of the cells is based on clustering the local...
High-throughput cell measurement techniques producing images of cell populations have raised a need for accurate automated image analysis methods. Validating the analysis methods used for automated cytometry is an issue yet to be solved. Manual validation, being an exhaustively laborious task, enables comparison but does not provide solution for large scale analysis. By creating a parametric model...
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