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Lung cancer prediction by deep learning approach

Principal Investigator
Name
Xiaokang Wang
Degrees
Ph.D.
Institution
University of California,Davis
Position Title
Research assistant
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-273
Initial CDAS Request Approval
Jan 26, 2017
Title
Lung cancer prediction by deep learning approach
Summary
Deep learning approach has been successfully applied in object detection, image classification and computer vision tasks. Deep learning approach will stand out if massive data is available to train a deep neural network. The goal of my project is to build a deep neural network to classify CT scanning images of a lung into two categories, benign and malignant. To achieve this goal, I need to first collect tons of CT images labeled by doctors. With the images in place, a cluster with GPU will be used to train a deep neural network. The final product will be a virtual classifier, which takes in multiples CT images of a person's lung, predicting the health state of his/her lung.
Aims

The aim of my project is to build a virtual classifier using deep learning approach. The classifier will take in multiples CT images of a person's lung, predicting the health state of his/her lung.

Collaborators

No collaborator.