The intervention of medical imaging has significantly improved early diagnosis of breast
cancer. Different radiological and microscopic imaging modalities are frequently utilized by …

Breast tumor segmentation from ultrasound images is one of the key steps that help us
characterize and localize tumor regions. However, variable tumor morphology, blurred …

Breast cancer (BC) is the leading cause of death among women worldwide. Early detection
and diagnosis of BC can help significantly reduce the mortality rate. Ultrasound (US) can be …

Ultrasonography is an important routine examination for breast cancer diagnosis, due to its
non-invasive, radiation-free and low-cost properties. However, the diagnostic accuracy of …

Breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays an
important role in the screening and treatment evaluation of high-risk breast cancer. The …

As the new generation of breast cancer screening tools, automated breast ultrasound
(ABUS) has some difficulties of the long interpretation time in clinical application. A computer …

Manually segmenting breast lesion images poses a labor-intensive and expensive
undertaking for radiologists. Therefore, the adoption of an automated diagnostic approach …

Automatic and accurate medical image segmentation is a crucial step for clinical diagnosis
and treatment planning of diseases. The advanced convolutional neural network (CNN) …

Tumor segmentation in 3D automated breast ultrasound (ABUS) plays an important role in
breast disease diagnosis and surgical planning. However, automatic segmentation of …

Deep supervision, or known as' intermediate supervision'or'auxiliary supervision', is to add
supervision at hidden layers of a neural network. This technique has been increasingly …