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Algorithmic scatter correction in dual-energy digital mammography.

Xi Chen1, Robert M Nishikawa, Suk-tak Chan

  • 1Institute of Image Processing and Pattern Recognition, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.

Medical Physics
|December 11, 2013
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Summary

A new algorithmic method effectively corrects scatter in dual-energy digital mammography (DEDM) without extra patient exposure. This technique improves calcification detection by reducing background noise and enhancing contrast-to-noise ratio (CNR).

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Area of Science:

  • Medical Imaging
  • Radiology
  • Biomedical Engineering

Background:

  • Small calcifications are critical early indicators of breast cancer.
  • Dual-energy digital mammography (DEDM) enhances calcification detectability by improving tissue contrast.
  • X-ray scatter degrades DEDM image quality, necessitating correction methods.

Purpose of the Study:

  • To develop an algorithmic scatter correction method for DEDM.
  • To achieve scatter correction without requiring additional X-ray exposure to patients.
  • To improve the accuracy and reliability of DEDM for breast cancer detection.

Main Methods:

  • Developed an algorithmic approach leveraging the low spatial variation of scattered radiation and the prevalence of non-calcification pixels.
  • Estimated and utilized the scatter fraction to remove scatter from DEDM images.
  • Implemented and compared the algorithmic method with the pinhole-array interpolation method using phantoms on a commercial DEDM system.

Main Results:

  • The algorithmic scatter correction significantly reduced the root-mean-square of background DE calcification signals from 1962 μm to 194 μm.
  • Reduced the range of background DE calcification signals by 58%.
  • Enabled a reduction in the minimum visible calcification size from 380 μm to 280 μm with scatter correction and denoising.

Conclusions:

  • The proposed algorithmic scatter correction effectively reduces background signals and improves the contrast-to-noise ratio (CNR) of calcifications in DEDM.
  • The method demonstrates comparable or superior performance to the pinhole-array interpolation method while being more convenient and avoiding extra patient exposure.
  • Further validation on structured backgrounds is recommended to fully assess the method's effectiveness in diverse clinical scenarios.