RT Journal Article
T1 Automated method for small-animal PET image registration with intrinsic validation
A1 Pascau González-Garzón, Javier
A1 Gispert, Juan Domingo
A1 Michaelides, Michael
A1 Thanos, Panayotis K.
A1 Volkow, Nora D.
A1 Vaquero López, Juan José
A1 Soto Montenegro, Mª Luisa
A1 Desco Menéndez, Manuel
AB We propose and compare different registration approaches to align small-animal PET studies and a procedure to validate the results by means of objective registration consistency measurements.Procedures: We have applied a registration algorithm based on information theory, usingdifferent approaches to mask the reference image. The registration consistency allows for the detection of incorrect registrations. This methodology has been evaluated on a test dataset(FDG-PET rat brain images).Results: The results show that a multiresolution two-step registration approach based on the use of the whole image at the low resolution step, while masking the brain at the high resolution step,provides the best robustness (87.5% registration success) and highest accuracy (0.67-mm average).Conclusions: The major advantages of our approach are minimal user interaction and automatic assessment of the registration error, avoiding visual inspection of the results, thus facilitating the accurate, objective, and rapid analysis of large groups of rodent PET images
PB Springer
SN 1536-1632 (print version)
SN 1860-2002 (electronic version)
YR 2009
FD 2009
LK https://hdl.handle.net/10016/12023
UL https://hdl.handle.net/10016/12023
LA eng
NO This work was supported by projects CIBER CB06/01/0079 (Ministerio de Sanidad y Consumo) and CDTEAM (CENIT program, Ministerio de Industria). Further support came from NIAAA Intramural Research Program (AA 11034 and AA07574, AA07611) and the US Department of Energy (DE-AC02-98CH10886)
DS e-Archivo
RD 18 may. 2024