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 …

Various deep learning methods have been proposed to segment breast lesions from
ultrasound images. However, similar intensity distributions, variable tumor morphologies …

Segmentation and classification of breast tumors in ultrasound (US) images is an important
application to deep neural networks. Unet architecture is recently developed for image …

Background and objective Breast lesions segmentation is an important step of computer-
aided diagnosis system. However, speckle noise, heterogeneous structure, and similar …

The advancements in deep learning technologies have produced immense contributions to
biomedical image analysis applications. With breast cancer being the common deadliest …

Breast lesion is a malignant tumor that occurs in the epithelial tissue of the breast. The early
detection of breast lesions can make patients for treatment and improve survival rate. Thus …

Globally, breast cancer occurs frequently in women and has the highest mortality rate.
Owing to the increased need for a rapid and reliable initial diagnosis of breast cancer …

Breast cancer is a significant health concern that remains one of the leading causes of
mortality in women worldwide. Convolutional Neural Networks (CNNs) have been shown to …

U-Net and its extensions have achieved great success in medical image segmentation.
However, due to the inherent local characteristics of ordinary convolution operations, U-Net …

Currently, the automatic segmentation of breast tumors based on breast ultrasound (BUS)
images is still a challenging task. Most lesion segmentation methods are implemented …