Effective Representation of Three-Dimension Nodules for False-Positive Reduction in Pulmonary Nodule Detection

Lung cancer is a high-mortality disease. Using Computer-based Automatic Detection (CADe) systems can detect pulmonary nodules to assist early diagnosis. An effective CADe system based on deep learning is often trained with sufficient labeled samples. ...

False-positive reduction is a crucial step of computer-aided diagnosis (CAD) system for pulmonary nodules detection and it plays an important role in lung cancer diagnosis. In this paper, we propose a novel cross attention guided multi-...

• A novel multi-scale feature fusion method based on cross attention is proposed.

This paper focuses on a novel approach for false-positive reduction (FPR) of nodule candidates in Computer-Aided Detection (CADe) systems following the suspicious lesions detection stage. Contrary to typical decisions in medical image analysis, ...