Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …

Chest X-ray radiography (CXR) is among the most frequently used medical imaging
modalities. It has a preeminent value in the detection of multiple life-threatening diseases …

Abstract Background and Objective: Chest radiographs (CXR) are in great demand for
visualizing the pathology of the lungs. However, the appearance of bones in the lung region …

Bone suppression is to suppress the superimposed bone components over the soft tissues
within the lung area of Chest X-ray (CXR), which is potentially useful for the subsequent lung …

Objective To compare the effects of bone suppression imaging using deep learning (BSp-
DL) based on a generative adversarial network (GAN) and bone subtraction imaging using a …

Purpose Accurate segmentation (separating diseased portions of the lung from normal
appearing lung) is a challenge in radiomic studies of non-neoplastic diseases, such as …

This study aims to propose a deep learning (DL)-based physical education course
recommendation system by combining the Internet of Things (IoT) technology and DL, to …

Purpose Although a novel deep learning software was proposed using post-processed
images obtained by the fusion between X-ray images of normal post-operative radiography …

Background and objectives Chest X-ray image (CXR) is vital for screening, preventing, and
monitoring various lung diseases. In particular, the early detection of lung cancer can …

Recently, some facilities have utilized the dual-energy subtraction (DES) technique for chest
radiography to increase pulmonary lesion detectability. However, the availability of the …