A new deep learning model shows promise in detecting and segmenting lung tumors, according to a study published today in Radiology. The findings of the study could have important implications for lung ...

By integrating spirometry with low-dose CT scans, physicians at Philadelphia-based Temple University Health System are identifying serious lung conditions, such as chronic obstructive pulmonary ...

In patients with head and neck squamous cell carcinoma (HNSCC), low-dose CT achieved higher sensitivity than chest x-ray for detecting lung metastases and second primary lung cancer, but patients ...

Low-dose CT screening in a high-risk population detected lung cancer in 2.0% of participants, with nearly 80% of cases diagnosed at stage I or II. The screening protocol demonstrated 97.0% ...

Lung cancer screening with low-dose CT could have saved tens of thousands of lives — if only we'd listened to the data back ...

Accurate detection and segmentation of lung tumors on CT images is crucial for tracking cancer growth, assessing treatment efficacy, and planning radiation therapy. Currently, qualified physicians ...

Population-weighted estimates showed that fewer than 18% of eligible patients actually got a low-dose CT scan for lung cancer ...

A total of 2% of the eligible population was diagnosed with lung cancer after a positive screen on baseline CT, amounting to a number needed to screen being 49. 2. The sensitivity of the low-dose CT ...

Due to the destructive nature of COPD on patients’ lungs and well-being, timely diagnosis is key, and integrating spirometry ...