Boundary aware semantic segmentation using pyramid-dilated dense U-Net for lung segmentation in computed tomography images

Aim: The main objective of this work is to propose an efficient segmentation model for accurate and robust lung segmentation from computed tomography (CT) images, even when the lung contains abnormalities such as juxtapleural nodules, cavities, and consolidation. Methodology: A novel deep learning-b...

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Autore principale:	S Akila Agnes
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Wolters Kluwer Medknow Publications 2023-01-01
Serie:	Journal of Medical Physics
Soggetti:	computed tomography image analysis convolutional neural network lung segmentation pyramid-dilated dense u-net semantic segmentation
Accesso online:	http://www.jmp.org.in/article.asp?issn=0971-6203;year=2023;volume=48;issue=2;spage=161;epage=174;aulast=Agnes
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