Academic Research using Deep Learning of PLCO's Lung data
Principal Investigator
Name
zean liu
Degrees
phd
Institution
Harbin Institute of Technology
Position Title
student
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCOI-1049
Initial CDAS Request Approval
Sep 8, 2022
Title
Academic Research using Deep Learning of PLCO's Lung data
Summary
We propose a new classification algorithm to address label-noise, class-imbalance, and multi-label issues. We want to validate on plco dataset. Our research interests are computer-aided diagnosis and medical image computing, using deep learning and computer vision methods to solve various clinical problems. In this project, we hope to use deep learning techniques to classify thoracic diseases in chest X-rays to assist radiologists in their diagnosis.
Aims
1. validate the algorithm proposed for label noise, class-imbalance and multi-label issues
2. improve classification performance
3. validate our deep learning method on the Lung Screening Abnormalities dataset
Collaborators
Yuanzhi Cheng
Chang Liu
Tantao
Related Publications
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Multi-Label Local to Global Learning: A Novel Learning Paradigm for Chest X-ray Abnormality Classification.
Liu Z, Cheng Y, Tamura S
IEEE J Biomed Health Inform. 2023 May 30; Volume PP PUBMED