Data Analysis and Tissue Type Assignment for Glioblastoma Multiforme. (3rd March 2014)

• Record Type: Journal Article
• Authors: Li, Yuqian; Pi, Yiming; Liu, Xin; Liu, Yuhan; Van Cauter, Sofie
• Other Names: Shen Bairong Academic Editor.
• Is Part Of: BioMed research international. Volume 2014(2014)
• Publication Date: 2014-03-03
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2014/762126
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Glioblastoma multiforme (GBM) is characterized by high infiltration. The interpretation of MRSI data, especially for GBMs, is still challenging. Unsupervised methods based on NMF by Li et al. (2013, NMR in Biomedicine ) and Li et al. (2013, IEEE Transactions on Biomedical Engineering ) have been proposed for glioma recognition, but the tissue types is still not well interpreted. As an extension of the previous work, a tissue type assignment method is proposed for GBMs based on the analysis of MRSI data and tissue distribution information. The tissue type assignment method uses the values from the distribution maps of all three tissue types to interpret all the information in one new map and color encodes each voxel to indicate the tissue type. Experiments carried out on in vivo MRSI data show the feasibility of the proposed method. This method provides an efficient way for GBM tissue type assignment and helps to display information of MRSI data in a way that is easy to interpret.