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

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.

Keywords

• Bioinformatics
• Cancer
• Health Sciences
• Systems biology
• Biotechnology and bioengineering
• Computer sciences