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Template-based automatic breast segmentation on MRI by excluding the chest region.

Muqing Lin1, Jeon-Hor Chen, Xiaoyong Wang

  • 1Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697-5020 and National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Department of Biomedical Engineering, School of Medicine, Shenzhen University, 518060 China.

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|December 11, 2013
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Summary

This study introduces a fully automatic MRI method for breast density quantification. The novel chest template-based approach accurately segments breast volume and fibroglandular tissue, showing high agreement with radiologist assessments.

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Area of Science:

  • Radiology
  • Medical Imaging
  • Biomedical Engineering

Background:

  • Semiautomatic methods are common for breast density quantification on MRI.
  • A fully automatic method is needed for improved efficiency and consistency.

Purpose of the Study:

  • To develop and evaluate a fully automatic chest template-based method for breast MRI segmentation.
  • To compare the accuracy of the automatic method against radiologist segmentation.

Main Methods:

  • A novel chest template-based segmentation approach was developed using nonfat-suppressed breast MRI from 31 healthy women.
  • The method utilizes chest body landmarks for initial breast boundary identification and 3D segmentation slice by slice.
  • Segmentation accuracy was evaluated by comparing automated results with radiologist-corrected volumes and tissue segmentation.

Main Results:

  • The algorithm achieved a mean difference of approximately 1% in segmented breast volume compared to radiologist corrections.
  • Total segmentation error (inclusion + exclusion) for breast volume averaged around 3%.
  • Fibroglandular tissue segmentation showed a mean difference of approximately 1% with a total error of about 3%.

Conclusions:

  • The automatic chest template-based method demonstrates reliable performance across various body and breast shapes and densities.
  • This technique offers a promising, accurate, and automated tool for MRI-based breast density segmentation.
  • The method's high accuracy and consistency suggest its potential for clinical application in breast density assessment.