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Breast Strain Imaging: A Cad Framework

  • Jasjit S. Suri
  • Ruey-Feng Chang
  • Wei-Liang Chen
  • Chia-Ling Tsai
  • Chii-Jen Chen
Part of the Topics in Biomedical Engineering. International Book Series book series (ITBE)

In 2D ultrasound Computer-Aided Diagnosis (CAD), the main emphasis is extraction of tumor boundaries and its classification into benign and malignant types. This provides a direct tool for breast radiologists and can even prevent breast biopsies, thereby reducing the number of false positives. The prerequisite for accurate breast boundary estimation in 2D breast ultrasound images is accurate segmentation of breast tumors and shape modeling. But this is a challenging task, because there is no set pattern of progression of tumors in the spatiotemporal domain. This chapter adapts a methodology based on geometric deformable models such as the level set, which has the ability to extract the topology of shapes of breast tumors. Using this framework, we extract several features of breast tumors and feed this set of information into a vector machine-based classifier for classification of breast disease. Our system demonstrates accuracy, sensitivity, specificity, PPV, and NPV values of 87, 85, 88, 82, and 89%, respectively.

Keywords

Positive Predictive Value Negative Predictive Value Strain Imaging Neighboring Image Shift Distance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Jasjit S. Suri
    • 1
  • Ruey-Feng Chang
    • 2
  • Wei-Liang Chen
    • 3
  • Chia-Ling Tsai
    • 3
  • Chii-Jen Chen
    • 3
  1. 1.Eigen LLCGrass ValleyUSA
  2. 2.Department of Computer Science and Information Engineering, Graduate InstituteNational Taiwan UniversityTaiwan
  3. 3.Department of Computer Science and Information EngineeringNational Chung Cheng UniversityTaiwan

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