Related Experiment Video
Updated: Apr 20, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
AutoSPET: an SPM plugin to automatize neuroimages PET analysis
Patrizia Vizza1, Giuseppe Tradigo, Giuseppe Lucio Cascini
1Department of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, 88100, Catanzaro (CZ), Italy.
Abstract:
Neuroimaging analysis supports clinicians in the diagnosis of neurological diseases by extracting information from digital images. Due to the large number of images generated by new devices (e.g. PET ones), there is a lot of effort in defining computer-based tools to analyze and classify (brain) radiological images. Statistical tools, such as SPM (for Statistical Parametric Mapping), are largely used by physicians for image analysis. Nevertheless, large datasets analysis requires repetitive steps, due to the lack of automatic procedures. E.g. SPM requires human intervention during long and complex steps.We here present a tool, called AutoSPET (for Automatic SPM analysis for PET images), which allows to perform SPM analyses on large sets of PET images. It works as a meta-component orchestrating interactions with SPM, Matlab and with SPM plugins via a unified user interface. AutoSPET has been tested with real clinical datasets and it is publicly available as an official SPM plugin on the SPM website.
More Related Videos
08:40Positron Emission Tomography Imaging for In Vivo Measuring of Myelin Content in the Lysolecithin Rat Model of Multiple Sclerosis
Published on: February 28, 2021
09:36In vivo Positron Emission Tomography to Reveal Activity Patterns Induced by Deep Brain Stimulation in Rats
Published on: March 23, 2022