Detection and Classification of MS Lesions in Multispectral MR Images

Quantitative analysis of patients with multiple sclerosis (MS) is an important issue in both diagnosis and therapy monitoring. We propose a new spectral signature detection approach for quantitative volumetric analysis of multispectral MRI. It is called constrained energy minimization (CEM) method, which is derived from the hyperspectral imaging processing. 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. The results show that the CEM method is a promising and effective spectral technique for lesions detection in multispectral MRI.