Back to Search Start Over

A deep learning based CT image analytics protocol to identify lung adenocarcinoma category and high-risk tumor area

Authors :
Liuyin Chen
Haoyang Qi
Di Lu
Jianxue Zhai
Kaican Cai
Long Wang
Guoyuan Liang
Zijun Zhang
Source :
STAR Protocols, Vol 3, Iss 3, Pp 101485- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Summary: We present a protocol which implements deep learning-based identification of the lung adenocarcinoma category with high accuracy and generalizability, and labeling of the high-risk area on Computed Tomography (CT) images. The protocol details the execution of the python project based on the dataset used in the original publication or a custom dataset. Detailed steps include data standardization, data preprocessing, model implementation, results display through heatmaps, and statistical analysis process with Origin software or python codes.For complete details on the use and execution of this protocol, please refer to Chen et al. (2022). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Details

Language :
English
ISSN :
26661667
Volume :
3
Issue :
3
Database :
Directory of Open Access Journals
Journal :
STAR Protocols
Publication Type :
Academic Journal
Accession number :
edsdoj.431c9580507a4858a2a16236e4c7ec3f
Document Type :
article
Full Text :
https://doi.org/10.1016/j.xpro.2022.101485