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Methods for the segmentation and classification of breast ultrasound images: a review

  • Review Paper
  • Published:
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Abstract

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 challenging task. In recent years, several methods for segmenting and classifying BUS images have been studied. These methods use BUS datasets for evaluation. In addition, semantic segmentation algorithms have gained prominence for segmenting medical images.

Methods

In this paper, we examined different methods for segmenting and classifying BUS images. Popular datasets used to evaluate BUS images and semantic segmentation algorithms were examined. Several segmentation and classification papers were selected for analysis and review. Both conventional and semantic methods for BUS segmentation were reviewed.

Results

Commonly used methods for BUS segmentation were depicted in a graphical representation, while other conventional methods for segmentation were equally elucidated.

Conclusions

We presented a review of the segmentation and classification methods for tumours detected in BUS images. This review paper selected old and recent studies on segmenting and classifying tumours in BUS images.

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Acknowledgements

This research is supported by the Thailand Research Fund; Grant RSA6280098 and the Center of Excellence in Biomedical Engineering of Thammasat University. Thanks to the anonymous referees of the review for valuable remarks.

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Authors and Affiliations

  1. School of ICT, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12000, Thailand

    Ademola E. Ilesanmi & Stanislav S. Makhanov

  2. Department of Radiology, Thammasat University, Pathum Thani, Thailand

    Utairat Chaumrattanakul

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  1. Ademola E. Ilesanmi
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Correspondence to Ademola E. Ilesanmi or Stanislav S. Makhanov.

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Ilesanmi, A.E., Chaumrattanakul, U. & Makhanov, S.S. Methods for the segmentation and classification of breast ultrasound images: a review. J Ultrasound 24, 367–382 (2021). https://doi.org/10.1007/s40477-020-00557-5

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