A Novel Expert System for Non-invasive Liver Iron Overload Estimation in Thalassemic Patients
- Resource Type
- Conference
- Authors
- Farruggia, Alfonso; Agnello, Luca; Toia, Patrizia; Murmura, Elena; Russo, Maria; Grassedonio, Emanuele; Midiri, Massimo; Vitabile, Salvatore
- Source
- 2014 Eighth International Conference on Complex, Intelligent and Software Intensive Systems Complex, Intelligent and Software Intensive Systems (CISIS), 2014 Eighth International Conference on. :107-112 Jul, 2014
- Subject
- Computing and Processing
Iron
Artificial neural networks
Liver
Magnetic resonance imaging
Expert systems
Neurons
Diseases
LIOMOT
MRI T2
Thalassemia
Artificial Neural Network
Expert System
OsiriX
- Language
Expert Systems can integrate logic based often on computational intelligence methods and they are used in complex problem solving. In this work an Expert System for classifying liver iron concentration in thalassemic patients is presented. In this work, an ANN is used to validate the output of the L.I.O.MO.T (Liver Iron Overload Monitoring in Thalassemia) method against the output of the state-of-the-art method based on MRI T2 assessment for liver iron concentration. The model has been validated with a dataset of 200 samples. The experimental Mean Squared Error results and Correlation show interesting performances. The proposed algorithm has been developed as a plug in for OsiriX Dicom Viewer.