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Updated: Jan 8, 2026

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Evaluación de la Calidad de Imagen de Imágenes Monoenergéticas Virtuales Basadas en Aprendizaje Profundo a partir de

Ke Li^1,2,3, Prashant Nagpal¹, Brian F Mullan¹

¹Department of Radiology, University of Wisconsin-Madison.

Journal of computer assisted tomography

|December 12, 2025

Resumen

Las imágenes monoenergéticas virtuales (VME) basadas en aprendizaje profundo a partir de tomografía computarizada de energía única (SECT) mejoran significativamente la calidad de imagen y la opacificación vascular de la angiografía pulmonar en comparación con la SECT estándar. Este avance ofrece capacidades diagnósticas mejoradas sin necesidad de tomografía computarizada de doble energía (DECT).

Palabras clave:

calidad de imagen de TC angiografía pulmonar por TC aprendizaje profundo imagenología monoenergética virtual

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