Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks

Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks

Abstract Objective The infiltration status of pulmonary ground-glass nodules (GGNs) exhibits significant variability, demanding tailored surgical strategies and individualized postoperative adjuvant therapies. This study explored the preoperative assessment of GGN infiltration status using computed...

Full description

Saved in:
Bibliographic Details
Main Authors: Kun Mei, Zikang Feng, Hui Liu, Min Wang, Chao Ce, Shi Yin, Xiaoying Zhang, Bin Wang
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Cancer
Subjects:
Neural network imaging
Pulmonary ground-glass nodule infiltrating status
Surgical method
Online Access:https://doi.org/10.1186/s12885-025-14027-w
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items