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Computer Vision Beyond the Visible Spectrum pp 241–269Cite as

Visualization and Segmentation Techniques in 3D Ultrasound Images

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Part of the book series: Advances in Pattern Recognition ((ACVPR))

Summary

Although ultrasonography is an important cost-effective imaging modality, technical improvements are needed before its full potential is realized for accurate and quantitative monitoring of disease progression or regression. 2D viewing of 3D anatomy, using conventional ultrasonography limits our ability to quantify and visualize pathology and is partly responsible for the reported variability in diagnosis and monitoring of disease progression. Efforts of investigators have focused on overcoming these deficiencies by developing 3D ultrasound imaging techniques using existing conventional ultrasound systems, reconstructing the information into 3D images, and then allowing interactive viewing of the 3D images on inexpensive desktop computers. In addition, the availability of 3D ultrasound images has allowed the development of automated and semi-automated segmentation techniques to quantify organ and pathology volume for monitoring of disease. In this chapter, we introduce the basic principles of 3D ultrasound imaging as well as its visualization techniques. Then, we describe the use of 3D ultrasound in interventional procedures and discuss applications of 3D segmentation techniques of the prostates, needles, and seeds used in prostate brachytherapy.

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Authors and Affiliations

  1. Robarts Research Institute, 100 Perth Drive, London, ON, N6A 5K8, Canada

    Aaron Fenster, Mingyue Ding, Ning Hu, Hanif M. Ladak, Guokuan Li, Neale Cardinal & Dónal B. Downey

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  1. Aaron Fenster
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  2. Mingyue Ding
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  3. Ning Hu
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  4. Hanif M. Ladak
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  5. Guokuan Li
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  6. Neale Cardinal
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  7. Dónal B. Downey
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Editors and Affiliations

  1. Center for Research in Intelligent Systems, University of California at Riverside, CA, USA

    Bir Bhanu PhD (Fellow IEEE, AAAS, IAPR, Senior Honeywell Fellow (Ex.) (Fellow IEEE, AAAS, IAPR, Senior Honeywell Fellow (Ex.)

  2. Department of Computer Science, University of Houston, TX, USA

    Ioannis Pavlidis PhD

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Fenster, A. et al. (2005). Visualization and Segmentation Techniques in 3D Ultrasound Images. In: Bhanu, B., Pavlidis, I. (eds) Computer Vision Beyond the Visible Spectrum. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/1-84628-065-6_8

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  • DOI: https://doi.org/10.1007/1-84628-065-6_8

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