Promptable segmentation of CT lung lesions based on improved U-Net and Segment Anything model (SAM)

BackgroundComputed tomography (CT) is widely used in clinical diagnosis of lung diseases. The automatic segmentation of lesions in CT images aids in the development of intelligent lung disease diagnosis.ObjectiveThis study aims to address the issue of imprecise segmentation in CT images due to the b...

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Veröffentlicht in:	Journal of X-ray science and technology Jg. 33; H. 6; S. 1015
Hauptverfasser:	Yan, Wensong, Xu, Yunhua, Yan, Shiju
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 01.11.2025
Schlagworte:	Algorithms Humans Image Processing, Computer-Assisted - methods Lung - diagnostic imaging Lung Diseases - diagnostic imaging Radiographic Image Interpretation, Computer-Assisted - methods Tomography, X-Ray Computed - methods attentional mechanisms lung lesions promptable segmentation deep neural networks
ISSN:	1095-9114, 1095-9114
Online-Zugang:	Weitere Angaben
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