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Алгоритмы распознавания клеток крови

Алгоритмы распознавания клеток крови

Abstract

Рассмотрена структура системы анализа медицинских изображений. Приведены принципиальная схема установки для проведения автоматизированных микроскопических исследований мазков крови, а также алгоритм работы системы распознавания клеток крови. Сформулированы основные задачи, решаемые при проведении морфологического анализа крови. Определены требования к алгоритму при определении лейкоцитарной формулы и обнаружении форменных элементов крови на мазке. Предложена модель цветояркостных характеристик для описания типичных изображений мазка крови. Определены пороговые значения размеров объектов при поиске клеток. Исследована гистограмма яркости типичного поля зрения. Описан двухэтапный алгоритм обнаружения клеток крови, а также алгоритм построения разделяющей прямой на плоскости относительных цветов. Приведены результаты экспериментов на реальных препаратах.Рассмотрены причины возникновения ошибок обнаружения

The structure of the medical image analysis system is considered. A schematic diagram of the system for automated microscopic studies as well as the algorithm of recognition of blood cells are shown. The main task to be solved during the morphological analysis of blood is formulated. The requirements are specified for the algorithm used for determining leukocyte counts and detecting blood cells. A model of color and brightness characteristics to describe typical images of a blood smear is offered. The threshold values of the object size at searching the cells are specified. The luminance histogram of a typical field of view is studied. Two-step algorithm for detecting blood cells as well as the algorithm for constructing a separating line are described. The results of the experiments on real samples are given. The causes of detection errors are considered

Keywords

АНАЛИЗ МАЗКОВ КРОВИ,АВТОМАТИЗИРОВАННАЯ МИКРОСКОПИЯ,ОБНАРУЖЕНИЕ КЛЕТОК КРОВИ,МАШИННОЕ ЗРЕНИЕ,ANALYSIS OF BLOOD SMEARS,AUTOMATED MICROSCOPY,DETECTION OF BLOOD CELLS,MACHINE VISION

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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
bronze