Detection of spectral signatures in multispectral MR images for classification

Chuin Mu Wang, Clayton Chi Chang Chen, Yi Nung Chung, Sheng Chih Yang, Pau Choo Chung, Ching Wen Yang, Chein I. Chang

Research output: Contribution to journalArticlepeer-review

40 Citations (Scopus)


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 from the minimum variance distortionless response in passive sensor array processing. It considers a bank of spectral channels as an array processing 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 c-means method for performance evaluation. The results show that the CEM method is a promising and effective spectral technique for MR image classification.

Original languageEnglish
Pages (from-to)50-61
Number of pages12
JournalIEEE Transactions on Medical Imaging
Issue number1
Publication statusPublished - 2003 Jan

All Science Journal Classification (ASJC) codes

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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