# Automatic Breast Ultrasound Image Segmentation: A Survey

arXiv: https://arxiv.org/abs/1704.01472 · HTML: https://mlsanity.com/paper/1704.01472/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Apr 2017.

## Built on by (most cited first, 15 of 15)

- [AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound Images](https://mlsanity.com/paper/2204.12077/) (2022)
- [RCA-IUnet: A residual cross-spatial attention guided inception U-Net model for tumor segmentation in breast ultrasound imaging](https://mlsanity.com/paper/2108.02508/) (2021)
- [Rethinking the Unpretentious U-net for Medical Ultrasound Image Segmentation](https://mlsanity.com/paper/2209.07193/) (2022)
- [ESKNet-An enhanced adaptive selection kernel convolution for breast tumors segmentation](https://mlsanity.com/paper/2211.02915/) (2022)
- [Multi-Slice Low-Rank Tensor Decomposition Based Multi-Atlas Segmentation: Application to Automatic Pathological Liver CT Segmentation](https://mlsanity.com/paper/2102.12056/) (2021)
- [A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images](https://mlsanity.com/paper/2109.14919/) (2021)
- [Optimizing Edge Detection for Image Segmentation with Multicut Penalties](https://mlsanity.com/paper/2112.05416/) (2021)
- [BAGNet: Bidirectional Aware Guidance Network for Malignant Breast lesions Segmentation](https://mlsanity.com/paper/2204.13342/) (2022)
- [CEmb-SAM: Segment Anything Model with Condition Embedding for Joint Learning from Heterogeneous Datasets](https://mlsanity.com/paper/2308.06957/) (2023)
- [Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation](https://mlsanity.com/paper/2109.12629/) (2021)
- [EMT-NET: Efficient multitask network for computer-aided diagnosis of breast cancer](https://mlsanity.com/paper/2201.04795/) (2022)
- [O2PF: Oversampling via Optimum-Path Forest for Breast Cancer Detection](https://mlsanity.com/paper/2101.05775/) (2021)
- [Decomposing and Coupling Saliency Map for Lesion Segmentation in Ultrasound Images](https://mlsanity.com/paper/2308.00947/) (2023)
- [BAAF: A benchmark attention adaptive framework for medical ultrasound image segmentation tasks](https://mlsanity.com/paper/2310.00919/) (2023)
- [Latent-CURE for Breast Cancer Diagnosis](https://mlsanity.com/paper/2606.29928/) (2026)

## Abstract (arXiv)

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 of BUS image segmentation seems to meet its bottleneck. The improvement of the performance is increasingly challenging, and only few new approaches were published in the last several years. It is the time to look at the field by reviewing previous approaches comprehensively and to investigate the future directions. In this paper, we study the basic ideas, theories, pros and cons of the approaches, group them into categories, and extensively review each category in depth by discussing the principles, application issues, and advantages/disadvantages.