Revisión crítica de los Métodos de Supresión Ósea en Imágenes de Rayos X de Tórax

Ernesto Santiesteban Torres; Eduardo  Garea Llano

Autores/as

Ernesto Santiesteban Torres Universidad Tecnológica de la Habana "José Antonio Echeverría"
Eduardo Garea Llano Centro de Neurociencias de Cuba

Palabras clave:

Aprendizaje profundo, Imágenes CXR; Maquinas de aprendizaje, Supresión Ósea

Resumen

El examen de imágenes de radiografía de tórax es un método de evaluación del grado de efectividad de los protocolos aplicados a pacientes de COVID-19 en estado grave o crítico. Un elemento que influye significativamente en la efectividad de estos exámenes es la presencia en las imágenes de los huesos que interfieren en la correcta detección y evaluación de las lesiones provocadas por la enfermedad. El trabajo tiene por objetivo el estudio crítico de los Métodos de Supresión Ósea (MSO) que han sido propuestos como paso para el pre-procesamiento de imágenes de radiografía de tórax. La metodología empleada se basó en la búsqueda, selección, revisión y análisis de los trabajos más actuales publicados en la temática. Se analizaron los trabajos más representativos. Se realizó un análisis del papel de la supresión ósea para mejorar la eficacia del diagnóstico. Se presentó una clasificación taxonómica de los métodos estudiados. Se realizó una propuesta de posible solución sobre el enfoque de aprendizaje no supervisado, en aras de mejorar el desempeño del diagnóstico tanto de los radiólogos como de sistemas automatizados.

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