MSTS-Net: malignancy evolution prediction of pulmonary nodules from longitudinal CT images via multi-task spatial-temporal self-attention network

Purpose Longitudinal CT images contain the law of lesion growth and evolution over time. Therefore, our purpose is to explore the growth and evolution law of pulmonary lesions in the time dimension to improve the performance of predicting the malignant evolution of pulmonary nodules. Methods In this...

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Veröffentlicht in:	International journal for computer assisted radiology and surgery 2023-04, Vol.18 (4), p.685-693
Hauptverfasser:	Song, Ping, Hou, Jiaxin, Xiao, Ning, Zhao, Jun, Zhao, Juanjuan, Qiang, Yan, Yang, Qianqian
Format:	Artikel
Sprache:	eng
Schlagworte:	Coders Computed tomography Computer Imaging Computer Science Datasets Evolution Health Informatics Humans Image Processing, Computer-Assisted - methods Image segmentation Imaging Lesions Lung - pathology Lung Neoplasms - diagnosis Medical imaging Medicine Medicine & Public Health Modules Multiple Pulmonary Nodules - diagnostic imaging Multiple Pulmonary Nodules - pathology Nodules Original Article Pattern Recognition and Graphics Performance enhancement Performance prediction Pulmonary lesions Radiology ROC Curve Surgery Tomography, X-Ray Computed - methods Vision
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