Background Recent advances in deep learning techniques have led to improved diagnostic
abilities in ophthalmology. A generative adversarial network (GAN), which consists of two …

Deep learning (DL) algorithms have rapidly become a robust tool for analyzing medical
images. They have been used extensively for medical image segmentation as the first and …

In medical imaging, segmentation plays a vital role towards the interpretation of X-ray
images where salient features are extracted with the help of image segmentation. Without …

A generative adversarial network (GAN) is one of the most significant research directions in
the field of artificial intelligence, and its superior data generation capability has garnered …

Background and Motivation: COVID-19 has resulted in a massive loss of life during the last
two years. The current imaging-based diagnostic methods for COVID-19 detection in …

Chest radiography (X-ray) is the most common diagnostic method for pulmonary disorders.
A trained radiologist is required for interpreting the radiographs. But sometimes, even …

In the clinical research, three-dimensional/volumetric anatomical structure of the human
body is very significant for diagnosis, computer-aided surgery, surgical planning, patient …

Generative models are becoming popular for the synthesis of medical images. Recently,
neural diffusion models have demonstrated the potential to generate photo-realistic images …

Deep learning techniques, particularly convolutional neural networks, have shown great
potential in computer vision and medical imaging applications. However, deep learning …

Automatic identification of salient features in large medical datasets, particularly in chest x-
ray (CXR) images, is a crucial research area. Accurately detecting critical findings such as …