Contrast enhancement and tissues classification of breast MRI using Kalman filter-based linear mixing method

Sheng Chih Yang, Chuin Mu Wang, Hsian He Hsu, Pau Choo Chung, Giu Cheng Hsu, Chun Jung Juan, Chien Shun Lo

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Much attention is currently focused on one of the newest breast examination techniques, breast MRI. Contrast-enhanced breast MRIs acquired by contrast injection have been shown to be very sensitive in the detection of breast cancer, but are also time-consuming and cause waste of medical resources. This paper therefore proposes the use of spectral signature detection technology, the Kalman filter-based linear mixing method (KFLM), which can successfully present the results as high-contrast images and classify breast MRIs into major tissues from four bands of breast MRIs. A series of experiments using phantom and real MRIs was conducted and the results compared with those of the commonly used c-means (CM) method and dynamic contrast-enhanced (DCE) breast MRIs for performance evaluation. After comparison with the CM algorithm and DCE breast MRIs, the experimental results showed that the high-contrast images generated by the spectral signature detection technology, the KFLM, were of superior quality.

Original languageEnglish
Pages (from-to)187-196
Number of pages10
JournalComputerized Medical Imaging and Graphics
Volume33
Issue number3
DOIs
Publication statusPublished - 2009 Apr 1

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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