Validation of Registration for Renal Dynamic Contrast Enhanced MRI Imaging

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.

Authors and Affiliations

Seniha Esen Yuksel *| Hacettepe University, Department of Electrical and Electronics Engineering, Ankara, Turkey.

Keywords

Related Articles

Long Term and Remote Health Monitoring with Smartphone

The basic aim of our work is to provide solutions with monitoring the heart beat rates of disabled or old people. And also we expect to help the people who have specific heart diseases like potential cardiac arrests...

An Efficient Document Categorization Approach for Turkish Based Texts

Since, it is infeasible to classify all the documents with human effort due to the rapid and uncontrollable growth in textual data, automatic methods have been approached in order to organize the data. Therefore a suppor...

A robust adaptive control of interleaved boost converter with power factor correction in wind energy systems

Power converters are generally utilized to convert the power from the wind sources to match the load demand and grid requirement to improve the dynamic and steady-state characteristics of wind generation systems and to i...

A region covariances-based visual attention model for RGB-D images

Existing computational models of visual attention generally employ simple image features such as color, intensity or orientation to generate a saliency map which highlights the image parts that attract human attention. I...

PID Parameters Prediction Using Neural Network for A Linear Quarter Car Suspension Control

Providing control for suspension systems in vehicles is an enhancing factor for comfort and safety. With the improvement of control conditions, it is possible to design a cost-efficient controller which will maintain opt...

Download PDF file
  • EP ID EP800
  • DOI 10.18201/ijisae.45496
  • Views 425
  • Downloads 23

How To Cite

Seniha Esen Yuksel * (2016). Validation of Registration for Renal Dynamic Contrast Enhanced MRI Imaging. International Journal of Intelligent Systems and Applications in Engineering, 4(3), 57-65. https://europub.co.uk/articles/-A-800