Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …

Medical image datasets are usually imbalanced due to the high costs of obtaining the data
and time-consuming annotations. Training a deep neural network model on such datasets to …

Mammography is the primary procedure for breast cancer screening, attempting to reduce
breast cancer mortality risk with early detection. Deep learning methods have shown strong …

The moving object segmentation (MOS) in videos with bad weather, irregular motion of
objects, camera jitter, shadow and dynamic background scenarios is still an open problem …

Medical imaging performs a vital function in unique medical programs. But, because of
multiple issues like price and radiation dose, the purchase of sure image modalities is …

Generative adversarial networks (GANs) are unsupervised Deep Learning approach in the
computer vision community which has gained significant attention from the last few years in …

Diabetic retinopathy is the consequence of advanced stages of diabetes, which can
ultimately lead to permanent blindness. An early detection of diabetic retinopathy is …

Deep learning based image segmentation has achieved the state-of-the-art performance in
many medical applications such as lesion quantification, organ detection, etc. However …

Computer-aided medical diagnosis is widely used to assist in the interpretation of medical
images. Early screening of diseases has a great value for the clinical diagnosis. However …

Objective: To compare the vessel geometry characteristics of color fundus photographs in
normal control and diabetes mellitus (DM) patients and to find potential biomarkers for early …