ДИНАМИКА ТЕЧЕНИЯ КОНЦЕВЫХ ЭЛЕМЕНТОВ ЦИЛИНДРИЧЕСКОГО ЛАЙНЕРА ДЛЯ ИМПУЛЬСНОГО СЖАТИЯ ПЛАЗМЫВ.П.Бахтин 1

Background Mobile phone screens can facilitate stimulation to various components of the visual system and many mobile apps are accepted as a means of providing clinical assessments for the oculo-visual system. Although many of these apps are intended for use in clinical settings, there is a growing number of apps in eye care developed for self-tests and eye exercises for lay people. These and other features, however, have not yet been well described. Objective Our objective was to identify, describe, and categorize mobile apps related to eye care that are available to users in the Canadian iTunes market. Methods We conducted an extensive search of the Apple iTunes Store for apps related to eye care. We used the terms “eye,” “eye care,” “vision,” and “eye test” and included apps that are targeted at both lay people and medical professionals. We excluded apps whose primary function is not related to eye care. Eligible apps were categorized by primary purpose, based on how they were described by their developers in the iTunes Store. Results Our search yielded 10,657 apps, of which 427 met our inclusion criteria. After removing duplicates, 355 unique apps were subject to further review. We assigned the eligible apps to three distinct categories: 39/355 apps (11.0%) were intended for use by medical professionals, 236 apps (66.5%, 236/355) were intended for use by lay people, and 80 apps (22.5%, 80/355) were intended for marketing eye care and eye-care products. We identified 9 subcategories of apps based on the descriptions of their primary functions. Apps for medical professionals fell into three subcategories: clinical calculators (n=6), clinical diagnostic tools (n=18), and education and networking apps for professionals (n=15). Apps for lay people fell into four subcategories: self-testing (n=153), eye exercises (n=30), patient tools and low vision aids (n=35), and apps for patient education (n=18). Mixed-use apps (n=80) were placed into two subcategories: marketing of individual practitioners or eye-care products (n=72) and marketing of multiple eye-care products or professional services. Conclusions The most extensive subcategory pertaining to eye care consisted of apps for use by lay people, especially for conducting self-tests (n=236). This study revealed a previously uncharacterized category of apps intended for use by doctors and patients, of which the primary goal is marketing of eye-care services and products (n=80).

Insufficient and controversial knowledge about the macular drusen (MD), a lack of scientifically proven management methods for drusen and their strong correlation with AMD active progression makes MD an important area of research.AIM:The purpose of the study – to assess clinical feature of MD using modern digital imaging technologies.MATERIAL AND METHODS:Patients with both hard and soft drusen were studied using fluorescein angiography, swept-source optical coherence tomography (OCT), OCT-angiography, autofluorescence (both short-wavelength and near infra-red), scanning laser ophthalmoscopy in Multicolor mode. The retina, choroid and vitreoretinal interface were assessed on 50 patients with AMD and drusen using different imaging modalities. An additional group of the study was presented by 5 patients with geographic atrophy (GA) formed as a result of soft drusen fading, where retrospective assessment of the OCT scans was performed with special attention to the signs of soft drusen regression associated with atrophy of the overlying RPE.RESULTS:Two types of hard drusen were defined as the reticular pseudodrusen and the cuticular drusen. The qualitative and comparative analysis of data for each type of MD was performed. Vitreoretinal interface evaluation demonstrated the correlation between vitreomacular adhesion and mixed reticular and cuticular drusen. The choroidal thickness assessment in 9 different macular sectors in drusenoid eyes does not reveal a significant difference with control group. All of the analysed drusen-faded-eyes initially had been presented with OCT patterns of “nascent” GA.CONCLUSION:The modern retinal imaging techniques enable new approach to the diagnostic differentiation and description of various macular drusen types. The value of these methods for AMD prognosis is yet to be further investigated.

this review presented advances in computer-assisted methods of retinal vessels caliber assessment. Current mathematical models and associated problems are discussed.

this review presented advances in computer-assisted methods of retinal vessels caliber assessment. Current mathematical mod els and associated problems are discussed.

Retinal pathology is a common cause of an irreversible decrease of central vision commonly found amongst senior population. Detection of the earliest signs of retinal diseases can be facilitated by viewing retinal images available from the telemedicine networks. To facilitate the process of retinal images, screening software applications based on image recognition technology are currently on the various stages of development. Purpose: To develop and implement computerized image recognition software that can be used as a decision support technology for retinal image screening for various types of retinopathies. Methods: The software application for the retina image recognition has been developed using C++ language. It was tested on dataset of 70 images with various types of pathological features (age related macular degeneration, chorioretinitis, central serous chorioretinopathy and diabetic retinopathy). Results: It was shown that the system can achieve a sensitivity of 73 % and specificity of 72 %. Conclusion: Automated detection of macular lesions using proposed software can significantly reduce manual grading workflow. In addition, automated detection of retinal lesions can be implemented as a clinical decision support system for telemedicine screening. It is anticipated that further development of this technology can become a part of diagnostic image analysis system for the electronic health records.

Retinal pathology is a common cause of an irreversible decrease of central vision commonly found amongst senior population. Detection of the earliest signs of retinal diseases can be facilitated by viewing retinal images available from the telemedicine networks. To facilitate the process of retinal images, screening software applications based on image recognition technology are currently on the various stages of development.Purpose: To develop and implement computerized image recognition software that can be used as a decision support technologyfor retinal image screening for various types of retinopathies.Methods: The software application for the retina image recognition has been developed using C++ language. It was tested on dataset of 70 images with various types of pathological features (age related macular degeneration, chorioretinitis, central serous chorioretinopathy and diabetic retinopathy).Results: It was shown that the system can achieve a sensitivity of 73 % and specificity of 72 %.Conclusion: Automated detection of macular lesions using proposed software can significantly reduce manual grading workflow. In addition, automated detection of retinal lesions can be implemented as a clinical decision support system for telemedicine screening. It is anticipated that further development of this technology can become a part of diagnostic image analysis system for the electronic health records.

Two series of experiments on the magnetic compressor (MC): with magnetic flow compression and electrical current output in the external loading are carried out. A megajoule capacitor battery is used as primary source of energy. The deformation dynamics of the liner material consisting of two flat plates, accelerated towards each other is investigated. The new scheme of electromagnetic acceleration, which automatically creates a magnetic flow in a compression zone, is used. At velocity of plates of 1 km/s the output electrical current of MC exceeds 4 MA. The results of modeling coincide with the experiment data with satisfactory accuracy. The MC device is intended for a power amplification of the inductive store of installation “MOL”.

In this paper we present an approach to achieve high accuracy of optic disk segmentation using information on the location of blood vessels (vessel map). Morphological preprocessing is employed to remove the vessels from the image and to compute the vessel map. Vessel map is combined with edge map to obtain robust initial approximation of OD boundary using circular Hough transform. We use this approximation to build 2D weight function for the edge map, which is then used in the active contour model. We introduce an additional step to perform correction of the contour; in this step, the active contour model includes pressure forces and soft elliptical constraint. Vessel map is used in calculation of the ellipse parameters and pressure values. The method was tested on 1240 publicly available retinal images, and manual labeling of the disk boundary by medical experts was used to assess its accuracy and compare it with other optic disk segmentation methods.

The problem of automated processing of retinal images for semiautomatic diagnosis of retinal diseases is considered in this paper. The main aspects of retinal image processing are discussed. Methods for non-uniform illumination correction, blood vessel detection and macula and optic disc segmentation, finding dark and light spots in the macula area are suggested.