日本質量分析学会 第66回質量分析総合討論会

Program

Oral Sessions

Day 4, May 18(Fri.) 14:25-15:05 Room C (Seiun 2)

Analysis of Measurement Data via Sparse Modeling

(Kyoto Univ.)
oToshiyuki Tanaka

Compressed sensing, a representative subject of sparse modeling, is a mathematical framework to solve an underdetermined linear equation on the basis of the assumption that the solution is sparse. It has wide applicability, since many physical measurement processes are formulated as a linear equation and there are many instances in real-world applications where quantities of interest are sparse in appropriately transformed domains. In this presentation we review sparse modeling and compressed sensing, as well as our recent study based on compressed sensing to visualize spatio-temporal distributions of chemical substances in vivo via magnetic resonance spectroscopic imaging.