Feature-enhanced adversarial semi-supervised semantic segmentation network for pulmonary embolism annotation

This study established a feature-enhanced adversarial semi-supervised semantic segmentation model to automatically annotate pulmonary embolism (PE) lesion areas in computed tomography pulmonary angiogram (CTPA) images. In the current study, all of the PE CTPA image segmentation methods were trained...

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Detalles Bibliográficos

Principais autores:	Ting-Wei Cheng, Yi Wei Chua, Ching-Chun Huang, Jerry Chang, Chin Kuo, Yun-Chien Cheng
Formato:	Artigo
Idioma:	Inglês
Publicado:	Elsevier 2023-05-01
Series:	Heliyon
Assuntos:	Pulmonary embolism Computed tomography pulmonary angiogram Semantic segmentation Semi-supervised learning Unlabeled images
Acceso en liña:	http://www.sciencedirect.com/science/article/pii/S240584402303267X
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