Computer Vision and Decision Support

  • Henry A. Swett
  • Maryellen L. Giger
  • Kunio Doi

Abstract

The preceding chapters describe basic mechanisms by which visual information is detected by the eye and brain, as well as fundamental principles of perception including texture and object recognition and cognitive processing. In addition, Chaps. 7 and 8 discuss computer processing techniques that may make specific image features easier to perceive. In this chapter, we consider ways that computers can directly extract features from images (computer vision), and understand their meaning and support human cognition (decision support). For example, in medical imaging, computer-vision techniques may be used to detect and characterize a possible abnormality (such as a tumor mass) in an image of the breast and then artificial intelligence (AI) techniques may be employed to merge the extracted features into a diagnostic decision regarding the possibility of malignancy. Computer processing techniques include image processing, image segmentation, and feature extraction. Decision support tools include rule-based expert systems, discriminant analysis, Bayesian methods, and neural networks among others.

Keywords

Computer Vision Decision Support Gray Level Interstitial Lung Disease Digital Radiography 
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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© Springer Science+Business Media New York 1993

Authors and Affiliations

  • Henry A. Swett
  • Maryellen L. Giger
  • Kunio Doi

There are no affiliations available

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