Predicting Malignancy and Invasiveness of Pulmonary Subsolid Nodules on CT Images Using Deep Learning

Predicting Malignancy and Invasiveness of Pulmonary Subsolid Nodules on CT Images Using Deep Learning

BackgroundTo develop and validate a deep learning–based model on CT images for the malignancy and invasiveness prediction of pulmonary subsolid nodules (SSNs).Materials and MethodsThis study retrospectively collected patients with pulmonary SSNs treated by surgery in our hospital from 2012 to 2018....

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Bibliographic Details
Main Authors: Tianle Shen, Runping Hou, Xiaodan Ye, Xiaoyang Li, Junfeng Xiong, Qin Zhang, Chenchen Zhang, Xuwei Cai, Wen Yu, Jun Zhao, Xiaolong Fu
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-07-01
Series:Frontiers in Oncology
Subjects:
pulmonary subsolid nodules
computed tomography
diagnosis
computer-aided diagnosis (CAD)
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2021.700158/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2021.700158/full

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