Dmitry Murashov

Technology for Automated Morphologic Analysis of Cytological Slides. Methods and Results

The information technology for automated morphologic analysis of the cytological slides, taken from patients with the lymphatic system tumors, was developed. The main components of the technology are: acquisition of cytological slides, method for segmentation of nuclei in the cytological slides, synthesis of the feature based nuclei description for subsequent classification, nuclei image analysis based on pattern recognition and scale-space techniques. The experiments confirmed efficiency of the developed technology. The discussion of the obtained results is given. The developed technology is implemented in the software system

Method for early diagnostics of lymphatic system tumors on the basis of the analysis of chromatin constitution in cell nucleus images

In this paper, a new criterion for early diagnostics of lymphatic system tumor from images of cell nuclei of lymphatic nodes is considered. A method for image analysis of chromatin structure is developed on the basis of the scale-space approach. A diagnostically important criterion is defined as a total amount of points of spatial intensity extrema in the families of blurred images generated by the given image of a cell nucleus. The procedure for calculating criterion values is presented. Testing of the obtained criterion is carried out.

A Technique for Computerised Brushwork Analysis

In this work, the problem of computer-assisted attribution of fine-art paintings based on image analysis methods is considered. A technique for comparing artistic styles is proposed. Textural features represented by histograms of brushstroke ridge orientation and local neighborhood orientation are used in this work to characterize painters artistic style. The procedures for feature extraction are developed and the parameters are chosen. The paintings are compared using three informative fragments segmented in a particular image. Selected image fragments are compared by information-theoretical dissimilarity measure. The technique is tested on images of portraits created in 17-19th centuries. The preliminary results of the experiments showed that the difference between portraits painted by the same artist is substantially smaller than one between portraits painted by different authors. The proposed technique may be used as a part of technological description of fine art paintings for attribution. The unsolved problems are pointed out and the directions of further research are outlined.

Image Registration Neural System for the Analysis of Fundus Topology

The developed system is a tool for high aperture imaging of the fundus. The obtained high resolution images preserve the topology of the blood vessels. The system is based on mosaicking a series of distinct low aperture fragments in order to obtain a high aperture image. Mosaicking is implemented by a neural network with stubborn learning taking into account the importance of the information of particular features. In mosaicking, the aberrations of the third order are partly compensated.

Segmentation Technique based on Information Redundancy Minimization.

In this paper, a problem of image segmentation quality is considered. The problem of segmentation quality is viewed as selecting the best segmentation from a set of images generated by segmentation algorithm at different parameter values. We use superpixel algorithm SLIC supplemented with the simple postprocessing procedure for generating a set of partitioned images with different number of segments. A technique for selecting the best segmented image is proposed. We propose to use information redundancy measure as a criterion for optimizing segmentation quality. It is shown that proposed method for constructing the redundancy measure provides it with extremal properties. Computing experiment was conducted using the images from the Berkeley Segmentation Dataset. The experiment confirmed that the segmented image corresponding to a minimum of redundancy measure produces the suitable dissimilarity when compared with the original image. The segmented image that was selected using the proposed criterion, gives the highest similarity with the ground-truth segmentations, available in the database.

Scale-Space Diagnostic Criterion for Microscopic Image Analysis

In this paper, a new criterion for diagnostics of hematopoietic tumors from images of cell nuclei of lymphatic nodes is presented. A method for image analysis of lymphatic node specimens is developed on the basis of the scale-space approach. A diagnostically important criterion is defined as a total amount of points of spatial intensity extrema in the families of blurred images generated by the given image of a cell nucleus. The procedure for calculating criterion values is presented. Testing of the obtained criterion is carried out using different classifiers. The accuracy of diagnostics is greater than 81% for collective classifiers.

A Technique for Extraction of Diagnostic Data from Cytological Specimens

In this paper, a possibility of developing a new criterion for diagnostics of hematopoietic tumors, such as chronic B-cell lymphatic leukemia, transformation of chronic B-cell lymphatic leukemia into lymphosarcoma, and primary B-cell lymphosarcoma, from images of cell nuclei of lymphatic nodes is considered. A method for image analysis of lymphatic node specimens is developed on the basis of the scale space approach. A diagnostically important criterion is defined as a total amount of points of spatial intensity extrema in the families of blurred images generated by the given image of a cell nucleus. The procedure for calculating criterion values is presented.