Intelligent diagnosis system based on artificial intelligence for malignancy grading of lung nodule CT images
Principal Investigator
Name
zhe quan
Degrees
Master of Engineering
Institution
Zhengzhou University
Position Title
student
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-1043
Initial CDAS Request Approval
Apr 13, 2023
Title
Intelligent diagnosis system based on artificial intelligence for malignancy grading of lung nodule CT images
Summary
We are a research team in medical image processing, with the goal of using artificial intelligence technology in medical image diagnosis。Our current research topic is to use the latest Lung-RADS1.1 diagnostic criteria, using artificial intelligence techniques such as convolutional neural networks, deep learning techniques, and hierarchical classification processing of lung nodules。Through the neural network we built, we can predict the stage of lung nodules in lung CT images, so as to help doctors make diagnoses。Because the training of neural networks requires a large number of datasets, we hope to apply the NLST dataset for our research。
Aims
1.Raw lung CT datasets were obtained and classified by lung nodule grade.
2.Image preprocessing of classified CT datasets.
3.Build neural networks such as VGG, RESNET, GOOGLENET.
4.The trained dataset is fed into the neural network for training and the performance indicators are observed
5.Compare with the same type of neural network to achieve optimal performance
6.The goal of the mission is to predict the level of lung nodules with more than 90% accuracy
Collaborators
HuiQin jiang Zhengzhou university