Medical image fusion based on non-negative matrix factorization

Daoming Zhang; Xianda Zhang

doi:10.1117/12.833956

30 October 2009 Medical image fusion based on non-negative matrix factorization

Daoming Zhang, Xianda Zhang

Proceedings Volume 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 74971Y (2009) https://doi.org/10.1117/12.833956
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Medical image fusion is a process of obtaining a new composite image from two or more source images which are from different modalities. In this paper, we proposed a novel medical image fusion scheme based on the non-negative matrix factorization (NMF) algorithm, the only resulted basis image is just the fused image. Since the CT and MRI images have a lot of pixels which are zeros, the NMF algorithm can not be employed directly. To overcome this difficulty, we first add a positive bias to the original data matrix and remove the bias from the resulted fusion image after the NMF procedure. The experiment results show that the proposed approach outperforms the existing wavelet-based methods and Laplacian pyramid-based methods.

Citation Download Citation

Daoming Zhang and Xianda Zhang "Medical image fusion based on non-negative matrix factorization", Proc. SPIE 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 74971Y (30 October 2009); https://doi.org/10.1117/12.833956

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KEYWORDS

Image fusion

Medical imaging

Image processing

Magnetic resonance imaging

Computed tomography

X-ray computed tomography

Data fusion

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