HomeProjectsBiomedical Sciences and Healthcare TechnologiesAutomatic Screening of Primary Lung Cancer

Automatic Screening of Primary Lung Cancer

Project Quick Facts

Principal Investigator

  • Prof. HENG Pheng Ann

    Department of Computer Science and Engineering

  • Funding

    Innovation and Technology Commission

Automated detection of pulmonary nodules via deep neural networks


Lung cancer has been the leading cause of cancer death worldwide. We propose a novel framework with 3D convolutional networks for automated detection of pulmonary nodules from low-dose CT scans, which is a challenging yet crucial task for lung cancer early diagnosis and treatment.

Problem to be solved:

Screening primary lung cancer by automatically detecting lung nodules from low-dose CT images


Lung cancer diagnosis via low-dose CT scan

Target Users:

Radiology department in hospitals

Lung nodule predictions with deep neural networks

Uniqueness and Competitive Advantages:

Our proposed framework consists of two stages: 1) candidate screening, and 2) false positive reduction. Different from previous standard deep learning based methods, we try to tackle the severe hard/easy sample imbalance problem in medical datasets and explore the benefits of localized annotations to regularize the learning.

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