title: Reconstruction and Feature Selection for Desorption Electrospray Ionization Mass Spectroscopy Imagery.
abstract: Desorption electrospray ionization mass spectrometry (DESI-MS) provides a highly sensitive imaging technique for differentiating normal and cancerous tissue at the molecular level. This can be very useful, especially under intra-operative conditions where the surgeon has to make crucial decision about the tumor boundary. In such situations, the time it takes for imaging and data analysis becomes a critical factor. Therefore, in this work we utilize compressive sensing to perform the sparse sampling of the tissue, which halves the scanning time. Furthermore, sparse feature selection is performed, which not only reduces the dimension of data from about 104to less than 50, and thus significantly shortens the analysis time. This procedure also identifies biochemically important molecules for pathological analysis. The methods are validated on brain and breast tumor data sets.
authors.affiliation: Department of Psychiatry, Harvard Medical School.
authors.forename: Yi
authors.initials: Y
authors.lastname: Gao
authors.affiliation: Department of Electrical and Computer Engineering, the University of Alabama, Birmingham.
authors.forename: Liangjia
authors.initials: L
authors.lastname: Zhu
authors.affiliation: Department of Neurosurgery, Brigham And Women's Hospital.
authors.forename: Isaiah
authors.initials: I
authors.lastname: Norton
authors.affiliation: Department of Neurosurgery, Brigham And Women's Hospital.
authors.forename: Nathalie Y R
authors.initials: NY
authors.lastname: Agar
authors.affiliation: Department of Electrical and Computer Engineering, the University of Alabama, Birmingham.
authors.forename: Allen
authors.initials: A
authors.lastname: Tannenbaum