Paper Info
Title
Elastic registration of prostate MR images based on state estimation of dynamical systems
Abstract
Magnetic resonance imaging (MRI) is being increasingly used for image-guided biopsy and focal therapy of prostate cancer. A combined rigid and deformable registration technique is proposed to register pre-treatment diagnostic 3 T magnetic resonance (MR) images, with the identified target tumor(s), to the intra-treatment 1.5 T MR images. The pre-treatment 3 T images are acquired with patients in strictly supine position using an endorectal coil, while 1.5 T images are obtained intra-operatively just before insertion of the ablation needle with patients in the lithotomy position. An intensity-based registration routine rigidly aligns two images in which the transformation parameters is initialized using three pairs of manually selected approximate corresponding points. The rigid registration is followed by a deformable registration algorithm employing a generic dynamic linear elastic deformation model discretized by the finite element method (FEM). The model is used in a classical state estimation framework to estimate the deformation of the prostate based on a similarity metric between pre- and intra-treatment images. Registration results using 10 sets of prostate MR images showed that the proposed method can significantly improve registration accuracy in terms of target registration error (TRE) for all prostate substructures. The root mean square (RMS) TRE of 46 manually identified fiducial points was found to be 2.40 +/- 1.20 mm, 2.51 +/- 1.20 mm, and 2.28 +/- 1.22 mm for the whole gland (WG), central gland (CG), and peripheral zone (PZ), respectively after deformable registration. These values are improved from 3.15 +/- 1.60 mm, 3.09 +/- 1.50 mm, and 3.20 +/- 1.73 mm in the WG, CG and PZ, respectively resulted from rigid registration. Registration results are also evaluated based on the Dice similarity coefficient (DSC), mean absolute surface distances (MAD) and maximum absolute surface distances (MAXD) of the WG and CG in the prostate images.
Year
DOI
Venue
2014
10.1117/12.2043884
Proceedings of SPIE
Keywords
Field
DocType
Prostate MR image registration,elastic model-based registration,motion compensation,focal ablation therapy,finite element method
Fiducial points,Computer vision,Motion compensation,Finite element method,Dynamical systems theory,Artificial intelligence,Root mean square,Prostate,Elasticity (economics),Magnetic resonance imaging,Physics
Conference
Volume
ISSN
Citations 
9034
0277-786X
2
PageRank 
References 
Authors
0.40
2
7
Name
Order
Citations
PageRank
Bahram Marami1666.09
Suha Ghoul231.45
Shahin Sirouspour322921.84
David W. Capson420729.98
Sean R H Davidson520.73
John Trachtenberg620.73
aaron fenster741.13