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Blind source separation for the computational analysis of dynamic oncological PET studies.

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National Technical University of Athens   

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Digital Library of National Technical University of Athens | Dspace@NTUA   

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Blind source separation for the computational analysis of dynamic oncological PET studies. (EN)
Thireou, T (EN)
Santos, A (EN)
Kontaxakis, G (EN)
Pavlopoulos, S (EN)
journalArticle (EN)
2014-03-01T01:23:40Z
2006 (EN)
The analysis of dynamic positron emission tomography (PET) studies provides clinically useful parametric information, but often requires complex and time-consuming compartmental or non-compartmental techniques. Independent component analysis (ICA), a statistical method used for feature extraction and signal separation, is applied to dynamic PET studies to facilitate the initial interpretation and visual analysis of these large image sequences. ICA produces parametric images, where structures with different kinetic characteristics are assigned opposite values and readily discriminated, improving the identification of lesions and facilitating the posterior detailed kinetic analysis. (EN)
Oncology (EN)
Data Interpretation, Statistical (EN)
scintiscanning (EN)
Humans (EN)
standard uptake values (EN)
Positron-Emission Tomography (EN)
article (EN)
Neoplasms (EN)
independent component analysis (EN)
Algorithms (EN)
neoplasm (EN)
Kinetics (EN)
positron emission tomography (EN)
kinetics (EN)
statistical analysis (EN)
human (EN)
algorithm (EN)
statistics (EN)
Oncology reports. (EN)
English
PROFESSOR D A SPANDIDOS (EN)
National Technical University of Athens
Digital Library of National Technical University of Athens | Dspace@NTUA
Κεντρική Βιβλιοθήκη Ε.Μ.Π.
Ιδρυματικό Αποθετήριο
Δημοσιεύσεις μελών Δ.Ε.Π. σε περιοδικά



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