Breast cancer is the most commonly diagnosed cancer type and is the leading cause of
cancer-related death among females worldwide. Breast screening and early detection are …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Microwave imaging (MWI) is a non-ionizing, non-invasive and an upcoming affordable
medical imaging modality. Over the last few decades, MWI has invited active research …

Globally, breast cancer is a major reason for female mortality. Due to the limitations of
current clinical imaging, the researchers are encouraged to explore alternative and …

With the prevalence of breast cancer among women and the shortcomings of conventional
techniques in detecting breast cancer at its early stages, microwave breast imaging has …

In the last five years alone, there has been an increasing number of operational microwave
breast imaging systems used in clinical trials, with increasingly large and diverse patient …

Bringing deep learning techniques to electromagnetic imaging is of interest considering its
great success in various fields. Deep neural nets however are known for being data hungry …

Microwave imaging is one of the rapidly developing frontier disciplines in the field of modern
medical imaging. The development of microwave imaging algorithms for reconstructing …

Microwave imaging has shown potential for breast cancer screening, but further evaluation
of the clinical viability of breast microwave imaging (BMI) systems is required. Previous …

Breast microwave imaging (BMI) is a potential breast cancer screening method. This
manuscript presents a novel iterative delay-and-sum (DAS) based reconstruction algorithm …