Validation of Registration for Renal Dynamic Contrast Enhanced MRI Imaging

Authors

  • Seniha Esen Yuksel Hacettepe University, Electrical and Electronics Engineering

DOI:

https://doi.org/10.18201/ijisae.45496

Keywords:

Validation, Inverse Transform, Renal, DCE-MRI

Abstract

In Dynamic Contrast Enhanced Resonance Imaging (DCE-MRI), abdomen is scanned repeatedly and rapidly after injection of a contrast agent. During data acquisition, collected images suffer from the motion induced by the patient if he/she moves or breathes heavily during the scan. Therefore, these images should be aligned accurately to correct the motion. Recently, mutual information (MI) registration has become the first tool to register renal DCE-MRI images before any further processing. However, MI registration is sensitive to initial conditions and optimization methods, and it is bound to fail under certain conditions such as extreme movement or noise in the image. Therefore, if automated image analysis for renal DCE-MRI is to enter the clinical settings, it is necessary to have validation strategies that show the limitations of registration models on known datasets. In this study, two methods are introduced for the validation of registration of renal DCE-MRI images. The first method demonstrates how to use the inverse transform to generate realistic looking DCE-MRI kidney images and use them in validation. The second method shows how to generate checkerboard images and how to evaluate the goodness of registration for real DCE-MRI images. These validation methods can be incorporated into the registration studies to quantitatively and qualitatively demonstrate the success and the limitations of registration models.

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Author Biography

Seniha Esen Yuksel, Hacettepe University, Electrical and Electronics Engineering

Assistant Professor, Electrical and Electronics Engineering Department.

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Published

13.07.2016

How to Cite

[1]
S. E. Yuksel, “Validation of Registration for Renal Dynamic Contrast Enhanced MRI Imaging”, Int J Intell Syst Appl Eng, vol. 4, no. 3, pp. 57–65, Jul. 2016.

Issue

Section

Research Article