Imaging-based Deep Learning for Lung Cancer Diagnosis and Staging

The Role of CNN Architecture-based Transfer Learning of Medical Imaging in Lung Cancer Diagnosis and Staging

Lung cancer diagnosis and staging are two fundamental and critical issue in clinical lung cancer management and therapeutic decision-making. Invasive procedures for pathologic analysis are gold standard for diagnosis and staging, however, invasive procedures related-complications are inevitable. Noninvasive medical imaging is a powerful tool, however there is almost no room for improvement just according to the experience of radiologist and clinician. The researchers will investigate the role of computer based deep learning of medical imaging in the diagnosis of lesion of lung, lymph node and other sites suspected with metastasis.

Radiologist

Inclusion Criteria:

• Pathological diagnosis of lung cancer
• PET/CT or CT examination before any cancer-specific treatment

Exclusion Criteria:

• A history of other malignancies