Dinapoli, Nicola, Alitto, Anna Rita, Vallati, Mauro, Gatta, Roberto, Autorino, Rosa, Boldrini, Luca, Damiani, Andrea and Valentini, Vincenzo (2015) Moddicom: a Complete and Easily Accessible Library for Prognostic Evaluations Relying on Image Features. In: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. EMBC . IEEE, pp. 771-774.

Decision Support Systems (DSSs) are increasingly
exploited in the area of prognostic evaluations. For predicting
the effect of therapies on patients, the trend is now to use image
features, i.e. information that can be automatically computed by
considering images resulting by analysis. The DSSs application
as predictive tools is particularly suitable for cancer treatment,
given the peculiarities of the disease –which is highly localised
and lead to significant social costs– and the large number of
images that are available for each patient.
At the state of the art, there exists tools that allow to handle
image features for prognostic evaluations, but they are not
designed for medical experts. They require either a strong
engineering or computer science background since they do not
integrate all the required functions, such as image retrieval and
storage. In this paper we fill this gap by proposing Moddicom,
a user-friendly complete library specifically designed to be
exploited by physicians. A preliminary experimental analysis,
performed by a medical expert that used the tool, demonstrates
the efficiency and the effectiveness of Moddicom.

IEEE_EBMCModdicom_features.pdf - Accepted Version

Download (1MB) | Preview


Downloads per month over past year

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email