Hierarchical non-negative matrix factorization applied to three-dimensional 3T MRSI data for automatic tissue characterization of the prostate
Abstract
In this study non-negative matrix factorization (NMF) was hierarchically applied to simulated and in vivo three-dimensional 3 T MRSI data of the prostate to extract patterns for tumour and benign tissue and to visualize their spatial distribution. Our studies show that the hierarchical scheme provides more reliable tissue patterns than those obtained by performing only one NMF level. We compared the performance of three different NMF implementations in terms of pattern detection accuracy and efficiency when embedded into the same kind of hierarchical scheme. The simulation and in vivo results show that the three implementations perform similarly, although one of them is more robust and better pinpoints the most aggressive tumour voxel(s) in the dataset. Furthermore, they are able to detect tumour and benign tissue patterns even in spectra with lipid artefacts. Copyright (C) 2016 John Wiley & Sons, Ltd.
Autore Pugliese
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Laudadio T.; Sava Anca R. C.; Sima D.M.; Wright A.J.; Heerschap A.; Mastronardi N.; Van Huffel S.
Titolo volume/Rivista
NMR in biomedicine
Anno di pubblicazione
2016
ISSN
0952-3480
ISBN
Non Disponibile
Numero di citazioni Wos
Nessuna citazione
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Numero di citazioni Scopus
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Settori ERC
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Codici ASJC
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