Linear intensity normalization of FP-CIT SPECT brain images using the α-stable distribution.
In this work, a linear procedure to perform the intensity normalization of FP-CIT SPECT brain images is presented. This proposed methodology is based on the fact that the histogram of intensity values can be fitted accurately using a positive skewed α-stable distribution. Then, the predicted α-stable parameters and the location-scale property are used to linearly transform the intensity values in each voxel. This transformation is performed such that the new histograms in each image have a pre-specified α-stable distribution with desired location and dispersion values. The proposed methodology is compared with a similar approach assuming Gaussian distribution and the widely used specific-to-nonspecific ratio. In this work, we show that the linear normalization method using the α-stable distribution outperforms those existing methods.
Dpt. Signal Theory, Networking and Communications, University of Granada, Spain.
Diego
D
Salas-Gonzalez
Juan M
JM
Górriz
Javier
J
Ramírez
Ignacio A
IA
Illán
Elmar W
EW
Lang
D001921:Brain / Q000000981:diagnostic imaging*; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019275:Radiopharmaceuticals; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*; D014326:Tropanes
D019275:Radiopharmaceuticals; D014326:Tropanes; C087552:2-carbomethoxy-8-(3-fluoropropyl)-3-(4-iodophenyl)tropane