Automatic lung nodule detection has great significance for treating lung cancer and
increasing patient survival. This work summarizes a critical review of recent techniques for …

Deep learning has an enormous impact on medical image analysis. Many computer-aided
diagnostic systems equipped with deep networks are rapidly reducing human intervention in …

Background and objective Detection of lung nodules is critical in CAD systems; this is
because of their similar contrast with other structures and low density, which result in the …

Early detection of lung cancer is an effective way to improve the survival rate of patients. It is
a critical step to have accurate detection of lung nodules in computed tomography (CT) …

Abstract Computer Aided Diagnosis (CAD) systems for automatic detection of pulmonary
diseases and lung cancer mainly depend on the segmentation of different pulmonary …

Lung cancer is the most prevalent and deadly oncological disease in the world, but a timely
detection of lung nodules can greatly improve the survival rate of this disease. However, due …

Background The study was conducted to evaluate the performance of a state‐of‐the‐art
commercial deep learning‐based computer‐aided diagnosis (DL‐CAD) system for detecting …

Objective To evaluate the performance of a deep learning-based computer-aided detection
(DL-CAD) system in a Chinese low-dose CT (LDCT) lung cancer screening program …

Detecting lung nodules with low-dose computed tomography (CT) can predict the future risk
suffering from lung cancers. However, there are a few studies on lung nodules with low-dose …

Pulmonary nodule detection has a significant impact on early diagnosis of lung cancer. To
effectively detect pulmonary nodules from interferential vessels in chest CT datasets, this …