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Automatic Lung Abnormality Detection and Classification based on Chest X-rays

Principal Investigator
Name
Lin Yang
Degrees
Ph.D.
Institution
University of Florida
Position Title
Associate Professor
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCO-370
Initial CDAS Request Approval
Jun 19, 2018
Title
Automatic Lung Abnormality Detection and Classification based on Chest X-rays
Summary
Chest X-rays are the most commonly used procedures for diagnosing lung diseases. However, to accurately and automatically detect abnormal lung regions and their subtypes is still a challenge. To address this issue, we aim to propose an efficient and accurate framework for lung abnormality detection and classification using deep learning techniques.
Aims

-Develop computer-aided techniques to perform lung abnormality detection and classification through convolutional neural networks
-Benchmark against existing lung abnormalities detection and classification methods

Collaborators

University of Florida