Name
Title | ||
|---|---|---|
A statistical model-based technique for accounting for prostate gland deformation in endorectal coil-based MR imaging. |
Abstract | ||
|---|---|---|
In prostate brachytherapy procedures, combining high-resolution endorectal coil (ERC)-MRI with Computed Tomography (CT) images has shown to improve the diagnostic specificity for malignant tumors. Despite such advantage, there exists a major complication in fusion of the two imaging modalities due to the deformation of the prostate shape in ERC-MRI. Conventionally, nonlinear deformable registration techniques have been utilized to account for such deformation. In this work, we present a model-based technique for accounting for the deformation of the prostate gland in ERC-MR imaging, in which a unique deformation vector is estimated for every point within the prostate gland. Modes of deformation for every point in the prostate are statistically identified using a set of MR-based training set (with and without ERC-MRI). Deformation of the prostate from a deformed (ERC-MRI) to a non-deformed state in a different modality (CT) is then realized by first calculating partial deformation information for a limited number of points (such as surface points or anatomical landmarks) and then utilizing the calculated deformation from a subset of the points to determine the coefficient values for the modes of deformations provided by the statistical deformation model. Using a leave-one-out cross-validation, our results demonstrated a mean estimation error of 1mm for a MR-to-MR registration. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/EMBC.2012.6347218 | EMBC |
Keywords | Field | DocType |
erc-mr imaging,prostate shape deformation,endorectal coil-based mr imaging,biomechanics,computerised tomography,nonlinear deformable registration,statistical analysis,brachytherapy,ct images,surface points,computed tomography,malignant tumors,leave-one-out cross-validation,high-resolution endorectal coil-mri,prostate gland deformation,mr-based training set,mean estimation error,prostate brachytherapy,biomedical mri,deformation,deformation vector,anatomical landmarks,tumours,image registration,biological organs,statistical model-based method,vectors,medical image processing,mr-to-mr registration | Mr imaging,Accounting,Computer science,Brachytherapy,Electromagnetic coil,Prostate,Statistical model,Deformation (mechanics),Prostate brachytherapy,Image registration | Conference |
Volume | ISSN | ISBN |
2012 | 1557-170X | 978-1-4577-1787-1 |
Citations | PageRank | References |
1 | 0.35 | 1 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amir M Tahmasebi | 1 | 1 | 0.35 |
| Reza Sharifi | 2 | 1 | 0.35 |
| Harsh Agarwal | 3 | 5 | 1.26 |
| Baris Turkbey | 4 | 3 | 1.73 |
| Marcelino Bernardo | 5 | 1 | 0.35 |
| Peter Choyke | 6 | 1 | 0.35 |
| Peter Pinto | 7 | 29 | 4.18 |
| Bradford J. Wood | 8 | 11 | 2.43 |
| Jochen Kruecker | 9 | 161 | 15.19 |