• AutoSPET (Automatic SPM tool invocation for PET analysis images)
  • Requirements
  • Resources
  • Results
  • Team People and Roles

AutoSPET (Automatic SPM tool invocation for PET analysis images)

The purpose of this study was to make use of tools such as Java and MatLab, for the realization of communication interfaces for both languages, with the task of optimizing procedures characterized by manual and burdensome processes from the point of view of time related to statistical analysis of PET data. 

AutoSPET (Automatic SPM tool invocation for PET analysis images), is a useful graphical user interface to improve efficiency in running SPM experi- ments. It is an interface developed in Java, allowing to integrate SPM, Matlab (i.e. the engine of SPM), MarsBaR and any other SPM plug-in. It manages all phases of PET statistical analysis, as shown in Figure 9, and allows to evaluate and run parametrized tests in parallel.

The application was made on the entire workflow, starting from the conversion of DICOM files, continuing on the part of pre-processing/statistics and ending finally with the running of the algorithm of classification of obtaining files mdata. The file mdata contains the coordinates of the ROI in three dimensions x-y-z, the spatial coordinates of the point at maximum intensity and the average value in the signal of the ROI. A portion of the study was to identify the way in which these values, initially non-extractable, could be acquired as the values on which to apply the classification algorithm in a completely automated and without manual intervention. The flow’s diagram shows the whole area of membership of the application.

The interaction between Matlab and Java application fully embraces their toolbox, and thanks this interaction was possible to automate the entire process. To create a development environment that could be interacting the two environments was necessary to use the MatlabControl, where a Java program running in a JVM different from MATLAB could launch and control a MATLAB session without user intervention. Achieved the communication of the two environments, it is passed with the realization of the phase of pre-processing by providing for:

  • Data files DICOM converter
  • Coregister
  • Normalise
  • Smoothing

As regards the part of statistics:

  • Factorial Design Specification
  • Model Estimation
  • Contrast Manager
  • Result Report

This is the representation of the software autospet. It 'a very intuitive tool, just perform simple operations and it will begin to interact with Matlab. The objective is to make the operations as described automated and to obtain in output the same results that are obtained by the classical procedure of SPM. The next section shows the link for the tutorial to help you understand the usage. The images show Autospet the initial presentation and the final part after completing all the steps.


Warning: This software tool implements some particularly time-consuming tasks, hence depending on your installed hardware, execution times could be long.


When you have satisfied the requirements, you can download Autospet directly from here, unzip the file, you must not perform any installation, just start the jar file to start the program.

Example dataset (PA2, PA3), contat project referent ""

Tutorial (Italian version, English version)

Contact us

Good Work


The results obtained can be quantified on procedural improvements. In a first test, using the classical procedure, SPM first, then Marsbar, and the classification algorithm, directly from the promt of Matlab. Later, the same tests were performed directly on Autospet. These tests have shown the same results obtained with the classical procedure, with the difference of a number of automation. Finally, the application is designed to help the work of a specialist user. The versatility of the programming language used for the realization of Autospet, makes possible the updating of new modules that will lead to an improvement in procedural automated.

Team People and Roles

The following table reports people working on this project and their roles.

Name Role Activity
Pierangelo Veltri, Ph.D.
Bioinformatics Expert
he is the project leader and supervises the development team. He is also one of the principal investigator.
Morelli Walter, Developer

Patrizia Vizza,

Giuseppe Tradigo,

Demetrio Messina,

Giuseppe Lucio Cascini