Szczegóły publikacji
Opis bibliograficzny
Variance stabilization of noncentral-chi data: application to noise estimation in MRI / Tomasz PIĘCIAK, Gonzalo Vegas-Sánchez-Ferrero, Santiago Aja-Fernández // W: ISBI 2016 [Dokument elektroniczny] : 2016 IEEE International Symposium on Biomedical Imaging: from nano to macro : April 13–16, 2016 : Prague, Czech Republic. — Wersja do Windows. — Dane tekstowe. — Piscataway : IEEE, cop. 2016. — 1 dysk Flash. — e-ISBN: 978-1-4799-2350-2. — S. 1376–1379. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 1379, Abstr. — Dod. ISBN: 978-1-4799-2349-6. — T. Pięciak - dod. afiliacja: Universidad de Valladolid, Spain
Autorzy (3)
- AGHPięciak Tomasz
- Vegas-Sánchez-Ferrero Gonzalo
- Aja-Fernández Santiago
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 97923 |
|---|---|
| Data dodania do BaDAP | 2016-05-30 |
| Rok publikacji | 2016 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencja | 2016 IEEE International Symposium on Biomedical Imaging |
Abstract
A variance-stabilizing transformation (VST) specifically designed for noncentral-chi (nc-χ) data is presented. The VST is derived to generate Gaussian-like distributed variates from nc-χ data. Two methods are proposed: (1) an analytic asymptotic model for high SNR; and (2) a robust numerical model to improve the performance for low SNR. As an application and proof of concept, the VST is used for the estimation of nonstationary noise fields in multiple coil MRI acquisitions. It is validated over accelerated data reconstructed using GRAPPA. The method is compared to the main state-of-the-art methods. Numerical results confirm the robustness of the method and its better performance for the whole range of SNRs.