Expert knowledge-infused deep learning for automatic lung nodule detection.
Journal:
Journal of X-ray science and technology
Published Date:
Jan 1, 2019
Abstract
BACKGROUND: Computer aided detection (CADe) of pulmonary nodules from computed tomography (CT) is crucial for early diagnosis of lung cancer. Self-learned features obtained by training datasets via deep learning have facilitated CADe of the nodules. However, the complexity of CT lung images renders a challenge of extracting effective features by self-learning only. This condition is exacerbated for limited size of datasets. On the other hand, the engineered features have been widely studied.