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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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A method based on moving least squares for XRII image distortion correction.

Shiju Yan1, Chengtao Wang, Ming Ye

  • 1Institute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai, China. yanshijv@sjtu.edu.cn

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|December 13, 2007
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Summary

A new integrated method corrects geometric distortions in X-ray image intensifier (XRII) images using moving least squares and polynomial fitting. This novel approach offers superior accuracy and reduced sensitivity to distortions compared to traditional methods.

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Area of Science:

  • Medical Imaging
  • Image Processing
  • Geometric Correction

Background:

  • Geometric distortions in X-ray Image Intensifier (XRII) images degrade diagnostic quality.
  • Traditional methods for correcting these distortions have limitations in accuracy and sensitivity.

Purpose of the Study:

  • To introduce and evaluate a novel integrated method for correcting geometric distortions in XRII images.
  • To compare the proposed method's performance against traditional local and global correction techniques.

Main Methods:

  • The proposed method integrates Moving Least Squares (MLS) and polynomial fitting.
  • Experiments were conducted on simulated and real XRII images.
  • Performance was assessed using mean-squared residual error at control and intermediate points.

Main Results:

  • The proposed method demonstrated robustness against pincushion and sigmoidal distortions.
  • It showed comparable or lower sensitivity to local distortions than traditional global methods.
  • While more sensitive to noise (above 0.1 pixels std. dev.), it maintained higher overall accuracy.
  • Accuracy was superior to traditional methods, with lower residual error on real 9-inch XRII images.

Conclusions:

  • The novel integrated method effectively corrects XRII geometric distortions.
  • It offers improved accuracy and reliability over existing techniques, particularly for complex distortions.
  • The method's performance is sensitive to noise levels but generally outperforms traditional approaches.