title: Unsupervised nosologic imaging for glioma diagnosis.
abstract: In this letter a novel approach to create nosologic images of the brain using magnetic resonance spectroscopic imaging (MRSI) data in an unsupervised way is presented. Different tissue patterns are identified from the MRSI data using nonnegative matrix factorization and are then coded as different primary colors (i.e. red, green, and blue) in an RGB image, so that mixed tissue regions are automatically visualized as mixtures of primary colors. The approach is useful in assisting glioma diagnosis, where several tissue patterns such as normal, tumor, and necrotic tissue can be present in the same voxel/spectrum. Error-maps based on linear least squares estimation are computed for each nosologic image to provide additional reliability information, which may help clinicians in decision making. Tests on in vivo MRSI data show the potential of this new approach.
authors.affiliation: School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; Department of Electrical Engineering and IBBT-Future Health Department, Katholieke Universiteit Leuven, Leuven 3001, Belgium. yuqianli@uestc.edu.cn
authors.forename: Yuqian
authors.initials: Y
authors.lastname: Li
authors.forename: Diana M
authors.initials: DM
authors.lastname: Sima
authors.forename: Sofie
authors.initials: S
authors.lastname: Van Cauter
authors.forename: Uwe
authors.initials: U
authors.lastname: Himmelreich
authors.forename: Anca R
authors.initials: AR
authors.lastname: Croitor Sava
authors.forename: Yiming
authors.initials: Y
authors.lastname: Pi
authors.forename: Yipeng
authors.initials: Y
authors.lastname: Liu
authors.forename: Sabine
authors.initials: S
authors.lastname: Van Huffel
mesh_terms: D001921:Brain / Q000473:pathology; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D016208:Databases, Factual; D005910:Glioma / Q000175:diagnosis* / Q000473:pathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016018:Least-Squares Analysis; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D059906:Neuroimaging / Q000379:methods*; D015203:Reproducibility of Results