Usefulness of digital images segmentation in pulmonary transplantation
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Fecha
2019
Autores
Gelvez-Almeida, E
Huérfano, Y
Vera, M
Vera, M I
Valbuena, O
Salazar-Torres, J
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Editor
IOP Publishing
Resumen
In the presence of pulmonary pathologies such as chronic obstructive pulmonary
disease, diffuse pulmonary disease and cystic fibrosis, among others, it is common to require
the removal or replacement of a portion of lungs. There are several requirements for both
donors and organ receivers (recipients) established in the literature. May be the main one is the
volume that the donor's lungs occupy in the thoracic cavity. This parameter is vital because if
the volume of the lungs exceeds the thoracic cavity of the recipients the transplant, logically, is
unfeasible for physical reasons such as the incompatibility between the receiver lung volume
and the donor lung volume. In this sense, the present paper proposes the creation of a hybrid
technique, based on digital image processing techniques application to raise the quality of the
information related to lungs captured in three-dimensional sequences of computed tomography
and for generating the morphology and the volumes of the lungs, belonging to a patient. During
the filtering stage median, saturated and gradient magnitude filters are applied with the purpose
of addressing the noise and artefacts images problems; whereas during the segmentation stage,
methods based on clustering processes are used to extract the lungs from the images. The
values obtained for the metric that assesses the quality of the hybrid computational technique
reflect its good performance. Additionally, these results are very important in clinical processes
where both the shapes and volumes of lungs are vital for monitoring some lung diseases that
can affect the normal lung physiology.
