Report for: A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data

Title	A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data
Published in	PLOS ONE, December 2013
DOI	10.1371/journal.pone.0083773
Pubmed ID	24376744
Authors	Sandra Ortega-Martorell, Héctor Ruiz, Alfredo Vellido, Iván Olier, Enrique Romero, Margarida Julià-Sapé, José D. Martín, Ian H. Jarman, Carles Arús, Paulo J. G. Lisboa
Abstract	The clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyzes single-voxel magnetic resonance spectra, which represent signal information in the frequency domain. Given that a single voxel may contain a heterogeneous mix of tissues, signal source identification is a relevant challenge for the problem of tumor type classification from the spectroscopic signal.

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Readers by professional status	Count	As %
Student > Ph. D. Student	12	28%
Student > Bachelor	9	21%
Researcher	7	16%
Student > Master	4	9%
Student > Doctoral Student	1	2%
Other	0	0%
Unknown	10	23%

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Mathematics	8	19%
Computer Science	8	19%
Biochemistry, Genetics and Molecular Biology	6	14%
Agricultural and Biological Sciences	4	9%
Medicine and Dentistry	3	7%
Other	4	9%
Unknown	10	23%

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