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  • Title: Contrast enhancement and tissues classification of breast MRI using Kalman filter-based linear mixing method.
    Author: Yang SC, Wang CM, Hsu HH, Chung PC, Hsu GC, Juan CJ, Lo CS.
    Journal: Comput Med Imaging Graph; 2009 Apr; 33(3):187-96. PubMed ID: 19135862.
    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.
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