Automatic breast ultrasound image segmentation: A survey

Automatic Breast Ultrasound Image Segmentation: A Survey

Breast cancer is one of the leading causes of cancer death among women worldwide. In clinical routine, automatic breast ultrasound (BUS) image segmentation is very challenging and essential for cancer diagnosis and treatment planning. Many BUS segmentation approaches have been studied in the last two decades, and have been proved to be effective on private datasets. Currently, the advancement o...

Automatic Medical Ultrasound Strain Image Segmentation for Breast Tumors

3D Ultrasound image segmentation: A Survey

Three-dimensional Ultrasound image segmentation methods are surveyed in this paper. The focus of this report is to investigate applications of these techniques and a review of the original ideas and concepts. Although many two-dimensional image segmentation in the literature have been considered as a threedimensional approach by mistake but we review them as a three-dimensional technique. We se...

Automatic Segmentation of Ultrasound Tomography Image

Ultrasound tomography (UST) image segmentation is fundamental in breast density estimation, medicine response analysis, and anatomical change quantification. Existing methods are time consuming and require massive manual interaction. To address these issues, an automatic algorithm based on GrabCut (AUGC) is proposed in this paper. The presented method designs automated GrabCut initialization fo...

A Benchmark for Breast Ultrasound Image Segmentation (BUSIS)

Breast ultrasound (BUS) image segmentation is challenging and critical for BUS Computer-Aided Diagnosis (CAD) systems. Many BUS segmentation approaches have been proposed in the last two decades, but the performances of most approaches have been assessed using relatively small private datasets with differ-ent quantitative metrics, which result in discrepancy in performance comparison. Therefore...