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Abstract #2401

A Supervised Artificial Neural Network Approach with Standardized Targets for IVIM Maps Computation

Alfonso Mastropietro1, Daniele Procissi2, Elisa Scalco1, Giovanna Rizzo1, and Nicola Bertolino2
1Istituto di Tecnologie Biomediche, Consiglio Nazionale delle Ricerche, Segrate, Italy, 2Radiology, Northwestern University, Chicago, IL, United States

Fitting the IVIM bi-exponential model is challenging especially at low SNRs and time consuming. In this work we propose a supervised artificial neural network approach to obtain reliable parameters estimation as demonstrated in both simulated data and real acquisition. The proposed approach is promising and can outperform, in specific conditions, other state-of-the-art fitting methods.

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