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Automatic detection of foreign objects in computed radiography.

J Xuan1, T Adali, Y Wang

  • 1University of Maryland Baltimore County, Department of Computer Science and Electrical Engineering, Baltimore, Maryland 21250, USA. xuanj@engr.umbc.edu

Journal of Biomedical Optics
|November 25, 2000
PubMed
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This study introduces a two-step method for detecting foreign objects in computed radiography (CR) images. Combining morphological filters and active contour models effectively identifies objects while minimizing false alarms.

Area of Science:

  • Medical Imaging
  • Computer Vision
  • Radiography

Background:

  • Computed radiography (CR) images present challenges for automatic object detection due to complex backgrounds.
  • Accurate identification of foreign objects in CR images is crucial for diagnosis and safety.

Purpose of the Study:

  • To develop and evaluate an effective two-step scheme for automatic foreign object detection in CR images.
  • To improve the accuracy and reduce false alarms in foreign object identification.

Main Methods:

  • Utilized morphological filters with feature incorporation (size, shape) to distinguish object candidates from background.
  • Employed active contour models to accurately delineate object boundaries and refine detection.
  • Combined morphological filtering and active contour models for a robust detection scheme.

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Main Results:

  • The proposed two-step scheme demonstrated effective automatic detection of foreign objects in CR images.
  • Achieved good sensitivity and specificity in identifying various types of foreign objects.
  • Provided accurate descriptions of object morphological characteristics.

Conclusions:

  • The integration of morphological filters and active contour models offers a powerful approach for foreign object detection in CR imaging.
  • This method enhances diagnostic capabilities by improving the reliability of object identification.