Purpose Breast cancer is the most common form of cancer among women worldwide.
Ultrasound imaging is one of the most frequently used diagnostic tools to detect and classify …

Breast cancer is the most commonly diagnosed cancer, which alone accounts for 30% all
new cancer diagnoses for women, posing a threat to women's health. Segmentation of …

Breast cancer is considered the most commonly diagnosed cancer globally and falls second
to lung cancer. For the early detection of breast tumors in women, breast cancer analysis …

Purpose Breast ultrasound (BUS) is one of the imaging modalities for the diagnosis and
treatment of breast cancer. However, the segmentation and classification of BUS images is a …

Rapid and precise segmentation of breast tumors is a severe challenge for the global
research community to diagnose breast cancer in younger females. An ultrasound system is …

Objectives To evaluate a deep convolutional neural network (dCNN) for detection,
highlighting, and classification of ultrasound (US) breast lesions mimicking human decision …

Background The role of a sensor element is to measure incident irradiance and record that
quantity as an image intensity value. However, physical constraints limit the maximum …

Automatic tumor segmentation in breast ultrasound (BUS) images is still a challenging task
because of many sources of uncertainty, such as speckle noise, very low signal-to-noise …

Breast tumor segmentation of ultrasound images provides valuable information of tumors for
early detection and diagnosis. Accurate segmentation is challenging due to low image …

We propose a novel initialization method designed for active contours (AC) and the level set
method (LSM), based on walking particles. The algorithm defines the seeds at converging …