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Pulmonary nodule detection with deep learning

Principal Investigator

Name
Ji Park

Degrees
M.D

Institution
JLK-INSPECTION

Position Title
Researcher

Email
jhpark3@jlk-inspection.com

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-551

Initial CDAS Request Approval
Aug 9, 2019

Title
Pulmonary nodule detection with deep learning

Summary
We aim to develop deep learning network for pulmonary nodule detection and lung nodule malignancy prediction.
Firstly, we intend to train a large number of CT Scans so that we could attempt to achieve high performances on our nodule detection model and then to build malignancy classification model with high prediction probability.
To evaluate our methods, we validate our models on test datasets whether it achieves solid performance results.
The algorithm is expected to achieve high performances on 1) nodule detection and 2) benign/malignancy classification

Aims

To build a deep learning model to detect pulmonary nodule with NLST dataset
To train an efficient convolutional network model for nodule malignancy prediction
To predict whether a region of interest is a nodule or non-nodule with our methods
To achieve high nodule malignancy accuracy

Collaborators

None