Mr. Rui Lopes Profile

Rui Lopes

at Elekta Ltd

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 8 March 2019 Paper

Deformable MRI-TRUS surface registration from statistical deformation models of the prostate

Shirin Shakeri, Cynthia Menard, Rui Lopes, Samuel Kadoury

Proceedings Volume 10951, 109511Y (2019) https://doi.org/10.1117/12.2512844

KEYWORDS: Prostate, Image segmentation, Magnetic resonance imaging, Statistical modeling, Image registration, Motion models, Biopsy, Prostate cancer, Image fusion, Data modeling

Read Abstract +

Transrectal ultrasound (TRUS) is considered the standard of care for imaging the prostate during biopsy and brachytherapy procedures. However, interpretation of TRUS images is challenging due to high specularity, making it difficult to recognize prostate boundaries. Image-guided brachytherapy and fusion-guided prostate biopsies require accurate non-rigid registration of magnetic resonance pre-operative image to intra-operative TRUS. State of the art techniques suggest semi-automated segmentation of the prostate on the TRUS images. However, due to the high variability, segmentation of the prostate is challenging. Segmentation errors could lead into poor localization of the biopsy target and can impact the registration of pre-operative images. In general, this kind of registration is challenging since the prostate anatomy undergoes motion due to TRUS probe pressure. In this paper, we propose a non-rigid surface registration approach for MR-TRUS fusion based on a statistical deformation model. Our method builds a statistical deformation model (SDM) of pre-operative to intra-operative deformations on a prostate dataset. In order to compute the fusion for an unseen MR-TRUS pair, the trained SDM is incorporated into the registration process to increase the fusion accuracy. The proposed approach is evaluated on a dataset of 23 patients with prostate cancer, for which the MRI-TRUS scans were available. We compared the proposed non-rigid SDM registration to non-rigid Iterative closest point (NICP) and rigid ICP approaches. Experiments demonstrate that the proposed SDM based method outperforms both NICP and ICP approaches, yielding a mean squared distance of 0.52 ± 0.26mm at the base, 0.45 ± 0.17mm mid-gland and 0.59 ± 0.13mm at the apex. These results show the advantage of integrating prior knowledge of deformation fields due to probe pressure for MR-TRUS fusion prostate interventions.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years