Study
            
                NLST
                (Learn more about this study)
            
 
            
            
                Project ID
                
                    
                        NLST-439
                    
                
            
            
                Initial CDAS Request Approval
                Sep 4, 2018
            
            Title
            Using deep learning approach to identify lung cancer and pulmonary tuberculosis
            
                Summary
                Pulmonary tuberculosis (TB) is a common misdiagnose for patients with lung cancer, CT scan is the one of most important aids for lung pulmonary disease detection. The initial object of our study is developing a deep neural network to classify CT scanning images for differential exclusion of tuberculosis and lung cancer. To achieve this goal, we will utilize the screening information to develop better predictors through TensorFlow.
            
            
                Aims
                The aim of my project is to develop a virtual classifier using deep learning approach. The classifier will automatically determine the tuberculosis and lung cancer based on CT images. It will help future cancer screening and accurate diagnosis of tuberculosis or malignancy.
Collaborators
                
                Hang Guo M.D. M.P.H.
Washington State University