A survey of computer-aided diagnosis of lung nodules from CT scans using deep learning
Y Gu, J Chi, J Liu, L Yang, B Zhang, D Yu… - Computers in biology …, 2021 - Elsevier
Lung cancer has one of the highest mortalities of all cancers. According to the National Lung
Screening Trial, patients who underwent low-dose computed tomography (CT) scanning …
Screening Trial, patients who underwent low-dose computed tomography (CT) scanning …
Survey on deep learning for pulmonary medical imaging
As a promising method in artificial intelligence, deep learning has been proven successful in
several domains ranging from acoustics and images to natural language processing. With …
several domains ranging from acoustics and images to natural language processing. With …
LungNet: A hybrid deep-CNN model for lung cancer diagnosis using CT and wearable sensor-based medical IoT data
Lung cancer, also known as pulmonary cancer, is one of the deadliest cancers, but yet
curable if detected at the early stage. At present, the ambiguous features of the lung cancer …
curable if detected at the early stage. At present, the ambiguous features of the lung cancer …
Knowledge-based collaborative deep learning for benign-malignant lung nodule classification on chest CT
The accurate identification of malignant lung nodules on chest CT is critical for the early
detection of lung cancer, which also offers patients the best chance of cure. Deep learning …
detection of lung cancer, which also offers patients the best chance of cure. Deep learning …
Semi-supervised adversarial model for benign–malignant lung nodule classification on chest CT
Classification of benign–malignant lung nodules on chest CT is the most critical step in the
early detection of lung cancer and prolongation of patient survival. Despite their success in …
early detection of lung cancer and prolongation of patient survival. Despite their success in …
MSCS-DeepLN: Evaluating lung nodule malignancy using multi-scale cost-sensitive neural networks
The accurate identification of malignant lung nodules using computed tomography (CT)
screening images is vital for the early detection of lung cancer. It also offers patients the best …
screening images is vital for the early detection of lung cancer. It also offers patients the best …
Multi-task deep model with margin ranking loss for lung nodule analysis
Lung cancer is the leading cause of cancer deaths worldwide and early diagnosis of lung
nodule is of great importance for therapeutic treatment and saving lives. Automated lung …
nodule is of great importance for therapeutic treatment and saving lives. Automated lung …
Efficient lung nodule classification using transferable texture convolutional neural network
Lung nodules are vital indicators for the presence of lung cancer. An early detection
enhances the survival rate of the patient by starting treatment at the right time. The detection …
enhances the survival rate of the patient by starting treatment at the right time. The detection …
Reinventing 2d convolutions for 3d images
There have been considerable debates over 2D and 3D representation learning on 3D
medical images. 2D approaches could benefit from large-scale 2D pretraining, whereas they …
medical images. 2D approaches could benefit from large-scale 2D pretraining, whereas they …
A lightweight multi-section CNN for lung nodule classification and malignancy estimation
The size and shape of a nodule are the essential indicators of malignancy in lung cancer
diagnosis. However, effectively capturing the nodule's structural information from CT scans …
diagnosis. However, effectively capturing the nodule's structural information from CT scans …