Abstract Recent advances in Deep Learning have largely benefited from larger and more
diverse training sets. However, collecting large datasets for medical imaging is still a …

Abstract Generative Adversarial Networks (GANs) have been widely applied in various
domains, including medical image analysis. GANs have been utilized in classification and …

Lung nodule segmentation plays a crucial role in early-stage lung cancer diagnosis, and
early detection of lung cancer can improve the survival rate of the patients. The approaches …

Lung cancer is one of the most fatal malignant diseases, which poses an acute menace to
human health and life. The accurate differential diagnosis of lung nodules is a vital step in …

Modern industry requires modern solutions for monitoring the automatic production of goods
and detecting defected materials. Smart monitoring of the functionality of the mechanical …

Purpose This paper reviews recent applications of Generative Adversarial Networks (GANs)
in Positron Emission Tomography (PET) imaging. Recent advances in Deep Learning (DL) …

This study proposes the integration of attention modules, feature-fusion blocks, and baseline
convolutional neural networks for developing a robust multi-path network that leverages its …

Novel methods are required to enhance lung cancer detection, which has overtaken other
cancer-related causes of death as the major cause of cancer-related mortality. Radiologists …

Early detection and identification of malignant lung nodules improve the survival of lung
cancer patients. The visual attributes such as subtlety, spiculation, and calcification of lung …

A tumor is a life-threatening disease that refers to the abnormal growth of cells in any part of
the human body. Early detection of this abnormality not only helps with appropriate …