Clasificación morfológica de eritrocitos en imágenes digitales de frotis de sangre periférica mediante deep learning
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Date
2022-01-27
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Universidad Antonio Nariño
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http://purl.org/coar/resource_type/c_7a1f
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Abstract
n hematology, the hemogram is one of the evaluative tests used with greater
regularity in medical practice, since it allows to evaluate and quantify the different types of
cells present in the blood. However, not all characteristics of blood cells can be detailed
with this test, which is why a microscopic inspection of the peripheral blood smear is
required. The manual exploration of the blood smear, allows to extract, among others,
qualitative information about the blood cells, by means of a visual inspection with the help
of the microscope; The inspection is a detailed and orderly process, which is carried out
with the aim of looking for morphological changes that make it possible to establish
differences between normality and abnormality.
Since it is carried out manually, the results of this type of classification, based on
qualitative parameters; they depend on the skill and experience of the evaluator, which can
lead to mistakes, time and money.
Taking into account the aforementioned, an erythrocyte classification method was
implemented in Matlab, based on morphological descriptors (diameter, perimeter, area,
solidity, circularity and concavity), from which a neural network was trained, from which a
percentage of accuracy of 83.3% is obtained.
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Colombia (Popayán, Cauca )