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Segmentation of prostate ultrasound images: the state of the art and the future directions of segmentation algorithms

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Abstract

Nowadays, prostate cancer has surpassed lung cancer as the most common type of cancer, segmentation of prostate ultrasound images is a critical step in the detection and planning treatment of prostate cancer. However, both ultrasound imaging characteristics and the physiology of the prostate make it difficult to determine the prostate boundaries in ultrasound images. In this paper, we provide a systematic review of advances in the field of ultrasound prostate image segmentation. In particular, three categories of algorithms are reviewed and compared, including edge-based segmentation, region-based segmentation, and those based on specific theoretical models. To understand the state of the art of different segmentations of the prostate ultrasound images, we conduct a literature analysis and a series of comparisons between different algorithms. The features and limitations of each category of segmentation algorithms are further discussed. Finally, we identified promising research directions in advancing the segmentation algorithms for the processing of ultrasound prostate images.

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Acknowledgements

This work was supported by the Natural Science Foundation of Heilongjiang Province (Grant No. LH2021E081), the Fundamental Research Foundation for Universities of Heilongjiang Province (Grant No. LGYC2018JQ016), China Postdoctoral Science Foundation Special Funded Project (Grant No. 2018T110313), and Heilongjiang Postdoctoral Science Foundation Special Funded Project (Grant No. LBH-TZ1705).

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Authors and Affiliations

  1. Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin, 150080, Heilongjiang, People’s Republic of China

    Jingang Jiang, Yafeng Guo & Jinke Wang

  2. Department of Civil and Mechanical Engineering, Purdue University Fort Wayne, Fort Wayne, IN, 46805, USA

    Zhuming Bi

  3. State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, 150001, Heilongjiang, People’s Republic of China

    Zhiyuan Huang

  4. Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, People’s Republic of China

    Guang Yu

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  1. Jingang Jiang
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Jiang, J., Guo, Y., Bi, Z. et al. Segmentation of prostate ultrasound images: the state of the art and the future directions of segmentation algorithms. Artif Intell Rev 56, 615–651 (2023). https://doi.org/10.1007/s10462-022-10179-4

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