Pulmonary nodule classification based on deep learning
Principal Investigator
Name
wan chaungye
Degrees
Master of Software Engineering
Institution
Medical Imaging Laboratory, School of Software, Nankai University
Position Title
Student
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-936
Initial CDAS Request Approval
Jul 15, 2022
Title
Pulmonary nodule classification based on deep learning
Summary
Our research focuses on deep learning based classification of pulmonary nodules, and we have recently proposed a method that can improve the classification of benign and malignant pulmonary nodules.This method firstly uses CNN to extract the features of pulmonary nodules, and then constructs the features into graphs. After some graph convolution and feature aggregation strategies, the over-smooth problem of graph convolution neural network is solved, and the performance of pulmonary nodules classification is improved.
Aims
Our research focuses on deep learning based classification of pulmonary nodules, and we have recently proposed a method that can improve the classification of benign and malignant pulmonary nodules.We hope to be able to verify on the NLST dataset to prove the robustness of our method.
Collaborators
Ling Ma - School of Software, Nankai University
Chuangye Wan - School of Software, Nankai University