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題名: Detection of Spectral Signatures in Multispectral MR Images for Classification
作者: Wang, Chuin-Mu;Chen, Clayton Chi-Chang;Chung, Yi-Nung;Yang, Sheng-Chih;Chung, Pau-Choo;Yang, Ching-Wen;Chang, Chein-I.
貢獻者: 電機工程學系
日期: 2003-01
上傳時間: 2012-07-02T02:06:25Z
出版者: IEEE
摘要: This paper presents a new spectral signature detection approach to magnetic resonance (MR) image classification. It is called constrained energy minimization (CEM) method, which is derived fromthe minimum variance distortionless response in passive sensor array processing. It considers a bank of spectral channels as an array of sensors where each spectral channel represents a sensor and object spectral signature in multispectral MR images are viewed as signals impinging upon the array. The strength of the CEM lies on its ability in detection of spectral signatures of interest
without knowing image background. The detected spectral signatures are then used for classification. The CEM makes use of a finite impulse response (FIR) filter to linearly constrain a desired object while minimizing interfering effects caused by other unknown signal sources. Unlike most spatial-based classification techniques, the proposed CEM takes advantage of spectral characteristics to achieve object detection and classification. A series of experiments is conducted and compared with the commonly used-means method for performance evaluation. The results showthat the CEM method is a promising and effective spectral technique for MR image classification.
關聯: IEEE Tran. on Medical Imaging, 22(1): 50-61
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