Simple Summary Lung cancer is the cause of many deaths that could have been avoided if
the disease had been detected at an early stage. This is possible thanks to the lung cancer …

In traditional clinical medicine, respiratory physicians or radiologists often identify the
location of lung nodules by highlighting targets in consecutive CT slices, which is labor …

Accurate and automatic detection of tiny lesions in medical imaging plays a critical role in
comprehensive cancer diagnosis, staging, treatment, follow-up, and prognosis. Numerous …

Existing pulmonary nodule detection methods often train models in a fully-supervised setting
that requires strong labels (ie, bounding box labels) as label information. However, manual …

The performance of modern U-shaped neural networks for medical image segmentation has
been significantly enhanced by incorporating Transformer layers. Although Transformer …

Purpose Lung cancer is the second most common cancer and the leading cause of cancer
death globally. Low dose computed tomography (LDCT) is the recommended imaging …

Lung cancer, which is on the rise, is the primary reason for mortality among cancer patients.
As stated by the World Health Organization, lung tumor is the second-deadliest type of …

Lung cancer stands as the leading cause of cancer related mortality worldwide. Precise and
automated identification of lung nodules through 3D Computed Tomography (CT) scans is …

Accurate segmentation of lung lesions in CT-scan images is essential to diagnose lung
cancer. The challenges in lung nodule diagnosis arise due to their small size and diverse …

The accurate position detection of lung nodules is crucial in early chest computed
tomography (CT)-based lung cancer screening, which helps to improve the survival rate of …