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Proceedings Paper

Improved registration of DCE-MR images of the liver using a prior segmentation of the region of interest
Author(s): Tian Zhang; Zhang Li; Jurgen H. Runge; Cristina Lavini; Jaap Stoker; Thomas van Gulik; Lucas J. van Vliet; Frans M. Vos
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Paper Abstract

In Dynamic Contrast-Enhanced MRI (DCE-MRI) of the liver, a series of images is acquired over a period of 20 minutes. Due to the patient’s breathing, the liver is subject to a substantial displacement between acquisitions. Furthermore, due to its location in the abdomen, the liver also undergoes marked deformation. The large deformations combined with variation in image contrast make accurate liver registration challenging. We present a registration framework that incorporates a liver segmentation to improve the registration accuracy. The segmented liver serves as region-of-interest to our in-house developed registration method called ALOST (autocorrelation of local image structure). ALOST is a continuous optimization method that uses local phase features to overcome space-variant intensity distortions. The proposed framework can confine the solution field to the liver and allow for ALOST to obtain a more accurate solution. For the segmentation part, we use a level-set method to delineate the liver in a so-called contrast enhancement map. This map is obtained by computing the difference between the last and registered first volume from the DCE series. Subsequently, we slightly dilate the segmentation, and apply it as the mask to the other DCE-MRI volumes during registration. It is shown that the registration result becomes more accurate compared with the original ALOST approach.

Paper Details

Date Published: 21 March 2016
PDF: 8 pages
Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 978443 (21 March 2016); doi: 10.1117/12.2216668
Show Author Affiliations
Tian Zhang, Technische Univ. Delft (Netherlands)
Zhang Li, National Univ. of Defense Technology (China)
Jurgen H. Runge, Academisch Medisch Centrum (Netherlands)
Cristina Lavini, Academisch Medisch Centrum (Netherlands)
Jaap Stoker, Academisch Medisch Centrum (Netherlands)
Thomas van Gulik, Academisch Medisch Centrum (Netherlands)
Lucas J. van Vliet, Technische Univ. Delft (Netherlands)
Frans M. Vos, Technische Univ. Delft (Netherlands)
Academisch Medisch Centrum (Netherlands)

Published in SPIE Proceedings Vol. 9784:
Medical Imaging 2016: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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