title: An advanced MRI and MRSI data fusion scheme for enhancing unsupervised brain tumor differentiation.
abstract: Proton Magnetic Resonance Spectroscopic Imaging (1H MRSI) has shown great potential in tumor diagnosis since it provides localized biochemical information discriminating different tissue types, though it typically has low spatial resolution. Magnetic Resonance Imaging (MRI) is widely used in tumor diagnosis as an in vivo tool due to its high resolution and excellent soft tissue discrimination. This paper presents an advanced data fusion scheme for brain tumor diagnosis using both MRSI and MRI data to improve the tumor differentiation accuracy of MRSI alone. Non-negative Matrix Factorization (NMF) of the spectral feature vectors from MRSI data and the image fusion with MRI based on wavelet analysis are implemented jointly. Hence, it takes advantage of the biochemical tissue discrimination of MRSI as well as the high resolution of MRI. The feasibility of the proposed frame work is validated by comparing with the expert delineations, giving mean correlation coefficients for the tumor source of 0.97 and the Dice score of tumor region overlap of 0.90. These results compare favorably against those obtained with a previously proposed NMF method where MRSI and MRI are integrated by stacking the MRSI and MRI features.
authors.affiliation: School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China. Electronic address: yuqianli@uestc.edu.cn.
authors.forename: Yuqian
authors.initials: Y
authors.lastname: Li
authors.affiliation: School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Liu
authors.affiliation: School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Feng
authors.initials: F
authors.lastname: Wei
authors.affiliation: STADIUS Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium.
authors.forename: Diana M
authors.initials: DM
authors.lastname: Sima
authors.affiliation: Department of Radiology, KU Leuven, Leuven, Belgium; Ziekenhuizen Oost Limburg, Genk, Belgium.
authors.forename: Sofie
authors.initials: S
authors.lastname: Van Cauter
authors.affiliation: Department of Imaging and Pathology, KU Leuven, Leuven, Belgium.
authors.forename: Uwe
authors.initials: U
authors.lastname: Himmelreich
authors.affiliation: School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Yiming
authors.initials: Y
authors.lastname: Pi
authors.affiliation: Center for Systems Biology, School of Electronic and Information Engineering, Soochow University, Suzhou, China.
authors.forename: Guang
authors.initials: G
authors.lastname: Hu
authors.affiliation: School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Yi
authors.initials: Y
authors.lastname: Yao
authors.affiliation: STADIUS Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium.
authors.forename: Sabine
authors.initials: S
authors.lastname: Van Huffel
mesh_terms: D014408:Biomarkers, Tumor / Q000032:analysis*; D001932:Brain Neoplasms / Q000737:chemistry / Q000175:diagnosis*; D005910:Glioma / Q000737:chemistry / Q000175:diagnosis*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D057054:Molecular Imaging / Q000379:methods; D064847:Multimodal Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D000069558:Unsupervised Machine Learning
chemical_list: D014408:Biomarkers, Tumor
keywords: Data fusion; Magnetic resonance imaging (MRI); Magnetic resonance spectroscopic imaging (MRSI); Non-negative matrix factorization (NMF)