This paper introduces a new method called constrained energy minimization (CEM) for classifying magnetic resonance (MR) images, which focuses on detecting spectral signatures.
The CEM method treats different spectral channels like sensors, enabling it to identify specific spectral signatures without needing to know the image background.
Experimental results demonstrate that CEM outperforms the commonly used c-means method, highlighting its effectiveness for MR image classification.