Automation of flow analysis in scleral vessels based on descriptive-associative algorithms.

Blood flow reflects the eye's health and is disrupted in many diseases. Many pathological processes take place at the cellular level like as microcirculation of blood in vessels, and the processing of medical images is a difficult recognition task. Existing techniques for measuring blood flow are limited due to the complex assumptions, equipment and calculations requirements.

[New mathematical method for automating the analysis of fluorescein angiograms of the human fundus].

Unlabelled: Specific software for digital image analysis is essential for adequate analysis and objectification of ophthalmic images, assessment of the prevalence of the pathological process, as well as for planning the amount of necessary medical intervention in various diseases.

Purpose: To develop a method for automatic analysis of angiographic images of the fundus for early diagnosis of vascular disorders and complications in a number of ophthalmic diseases.

Material And Methods: Initial angiograms of patients (=117) with vascular eye diseases and in healthy condition were analyzed in automatic mode using a new mathematical approach to digital processing of fundus fluorescein angiograms based on a three-stage algorithm for extracting information from images.

Development of fan-shaped tracker for single particle tracking.

With the development of super-resolution fluorescence microscopy, complex dynamic processes in living cells can be observed and recorded with unprecedented temporal and spatial resolution. Single particle tracking (SPT) is the most important step to explore the relationship between the spatio-temporal dynamics of subcellular molecules and their functions. Although previous studies have developed SPT algorithms to quantitatively analyze particle dynamics in cell, traditional tracking methods have poor performance when dealing with intersecting trajectories.

Extraction of nerve cells in images with herpetic infections.

In this paper, algorithms for extracting and diagnosis of nerve cells with herpetic infections are proposed. Degree of herpetic lesions is divided into four classes. Morphological characteristic of herpetic lesions for cell is accomplished by analyze cells structure.