Linear intensity normalization of FP-CIT SPECT brain images using the α-stable distribution

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2013-01, Vol.65, p.449-455
• Main Authors: Salas-Gonzalez, Diego, Górriz, Juan M., Ramírez, Javier, Illán, Ignacio A., Lang, Elmar W.
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Brain - diagnostic imaging; Brain Mapping - methods; Fundamental and applied biological sciences. Psychology; Humans; Image Processing, Computer-Assisted - methods; Radiopharmaceuticals; Tomography, Emission-Computed, Single-Photon - methods; Tropanes; Vertebrates: nervous system and sense organs
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2012.10.005

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. ► A linear procedure for intensity normalization using an α-stable distribution. ► α-stable parameters are estimated using the Maximum-Likelihood method. ► Location-scale property is used to linearly transform the voxel intensity values. ► The proposed method is compared with the widely used specific-to-non specific ratio. ► Intersubject differences in the non-specific regions are reduced.