Tensor based tumor tissue type differentiation using magnetic resonance spectroscopic imaging
| Autor: | Uwe Himmelreich, Nicolas Sauwen, S. Van Huffel, Diana M. Sima, H. N. Bharath, L. De Lathauwer |
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| Rok vydání: | 2016 |
| Předmět: |
Physics
Magnetic Resonance Spectroscopy SISTA medicine.diagnostic_test Brain Neoplasms Magnetic resonance spectroscopic imaging Magnetic resonance imaging Glioma medicine.disease Blind signal separation Tumor tissue Magnetic Resonance Imaging 3. Good health Matrix decomposition Nuclear magnetic resonance In vivo medicine Humans Algorithms High-Grade Glioma |
| Zdroj: | EMBC |
| ISSN: | 2694-0604 |
| Popis: | Magnetic resonance spectroscopic imaging (MRSI) has the potential to characterise different tissue types in brain tumors. Blind source separation techniques are used to extract the specific tissue profiles and their corresponding distribution from the MRSI data. A 3-dimensional MRSI tensor is constructed from in vivo 2D-MRSI data of individual tumor patients. Non-negative canonical polyadic decomposition (NCPD) with common factor in mode-1 and mode-2 and l(1) regularization on mode-3 is applied on the MRSI tensor to differentiate various tissue types. Initial in vivo study shows that NCPD has better performance in identifying tumor and necrotic tissue type in high grade glioma patients compared to previous matrix-based decompositions, such as non-negative matrix factorization and hierarchical non-negative matrix factorization. ispartof: pages:7003-7006 ispartof: Proc. Engineering in Medicine and Biology Society, 2015 37th Annual International Conference of the IEEE vol:2015 pages:7003-7006 ispartof: EMBC 2015 location:Milan, Italy date:Aug - Aug 2015 status: published |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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