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 …

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 …

Recent advances in transformer-based models have drawn attention to exploring these
techniques in medical image segmentation, especially in conjunction with the U-Net model …

Although having achieved great success in medical image segmentation, deep
convolutional neural networks usually require a large dataset with manual annotations for …

Pulmonary nodule detection, false positive reduction and segmentation represent three of
the most common tasks in the computer aided analysis of chest CT images. Methods have …

Although purely transformer-based architectures pretrained on large datasets are introduced
as foundation models for general computer vision tasks, hybrid models that incorporate …

Computer-aided lung cancer diagnosis (CAD) system on computed tomography (CT) helps
radiologists guide preoperative planning and prognosis assessment. The flexibility and …

Deep learning has emerged as a powerful tool for medical image analysis and diagnosis,
demonstrating high performance on tasks such as cancer detection. This literature review …

Lung cancer is one of the malignant tumor diseases with the fastest increase in morbidity
and mortality, which poses a great threat to human health. Low-Dose Computed …

The task of multimodal cancer detection is to determine the locations and categories of
lesions by using different imaging techniques, which is one of the key research methods for …