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 …

Due to the complicated structure of breast and poor quality of ultrasound images, accurately
and automatically locating regions of interest (ROIs) and segmenting tumors are challenging …

A huge amount of image data is being collected in real world sectors. Image data analytics
provides information about important facts and issues of a particular domain. But, it is …

Ultrasound imaging modality is used prominently for breast cancer screening and diagnosis
because of its safety, portability, ease of use and low cost. Over the years, computer-assisted …

Tumor segmentation is the foundation of breast ultrasound image analysis. However,
intensity inhomogeneity occurred in ultrasound images results in the ambiguous …

Image segmentation plays a crucial role in breast ultrasound (BUS) for breast cancer
detection. However, due to the heavy speckle noise, low contrast and shadowing effects of …

Segmentation of medical image, as the most essential and important step in the computer-
aided diagnosis system, can greatly influence the system performance. Better segmentation …

Breast cancer occurs to 8% women during their lifetime, and is a leading cause of death
among women. Breast ultrasound (BUS) image segmentation which is the essential process …

Breast tumor segmentation is useful to diagnose breast cancer. However, challenges, such
as intensity inhomogeneity and shadowing artifacts arise in this task. To address these two …

This paper introduces a parameter-automatically-optimized robust graph-based image
segmentation method (PAORGB) for segmenting breast tumors in ultrasonic images. The …