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Метод оценивания морфологических параметров сосудов на изображениях глазного дна на основе матриц видимости кривых

Метод оценивания морфологических параметров сосудов на изображениях глазного дна на основе матриц видимости кривых

Abstract

We discuss an approach to fundus image analysis that enables one to modify the diagnostic vessel parameters in such a way that the morphological peculiarities of tree-like structures are accounted for. A feature estimation method based on processing the geometric characteristics of central vessel line lobes is described. An approach relying upon partitioning the curves into lobes with use of the algorithm of visibility matrix construction is discussed. The approach developed makes it possible to construct a primary feature space that can be used for constructing morphological features invariant to various types of geometric distortions.

Описан подход, позволяющий модифицировать геометрические признаки таким образом, чтобы учесть морфологические особенности древовидных структур. В качестве примеров диагностических признаков будут использованы: 1) прямолинейность Рr и извитость I. После ввода изображение глазного дна подвергается обработке с целью получения центральных линий сосудов. Полученное дискретное представление центральной линии сосуда является исходными данными: {х}| i=1 N

Keywords

ОБРАБОТКА ИЗОБРАЖЕНИЙ, СОСУДЫ, ГЛАЗНОЕ ДНО, МОРФОЛОГИЯ, ПРИЗНАКИ, ГЕОМЕТРИЧЕСКИЕ ХАРАКТЕРИСТИКИ, СРЕДНЯЯ ЛИНИЯ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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