Artificial Neural Networks approach to pharmacokinetic model selection in DCE-MRI studies.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Published Date:

Abstract

PURPOSE: In pharmacokinetic analysis of Dynamic Contrast Enhanced MRI data, a descriptive physiological model should be selected properly out of a set of candidate models. Classical techniques suggested for this purpose suffer from issues like computation time and general fitting problems. This article proposes an approach based on Artificial Neural Networks (ANNs) for solving these problems.

Authors

  • Mohammad-Reza Mohammadian-Behbahani
    Department of Radiation Medicine Engineering, Shahid Beheshti University, Tehran, Iran; Department of Energy Engineering and Physics, Amir-Kabir University of Technology (Tehran Polytechnic), Tehran, Iran.
  • Ali-Reza Kamali-Asl
    Department of Radiation Medicine Engineering, Shahid Beheshti University, Tehran, Iran. Electronic address: a_kamali@sbu.ac.ir.