Open-source image registration for MRI-TRUS fusion-guided prostate interventions - Abstract

PURPOSE: We propose two software tools for non-rigid registration of MRI and transrectal ultrasound (TRUS) images of the prostate.

Our ultimate goal is to develop an open-source solution to support MRI-TRUS fusion image guidance of prostate interventions, such as targeted biopsy for prostate cancer detection and focal therapy. It is widely hypothesized that image registration is an essential component in such systems.

METHODS: The two non-rigid registration methods are: (1) a deformable registration of the prostate segmentation distance maps with B-spline regularization and (2) a finite element-based deformable registration of the segmentation surfaces in the presence of partial data. We evaluate the methods retrospectively using clinical patient image data collected during standard clinical procedures. Computation time and Target Registration Error (TRE) calculated at the expert-identified anatomical landmarks were used as quantitative measures for the evaluation.

RESULTS: The presented image registration tools were capable of completing deformable registration computation within 5 min. Average TRE was approximately 3 mm for both methods, which is comparable with the slice thickness in our MRI data. Both tools are available under nonrestrictive open-source license.

CONCLUSIONS: We release open-source tools that may be used for registration during MRI-TRUS-guided prostate interventions. Our tools implement novel registration approaches and produce acceptable registration results. We believe these tools will lower the barriers in development and deployment of interventional research solutions and facilitate comparison with similar tools.

Written by:
Fedorov A, Khallaghi S, Sánchez CA, Lasso A, Fels S, Tuncali K, Sugar EN, Kapur T, Zhang C, Wells W, Nguyen PL, Abolmaesumi P, Tempany C.   Are you the author?
Brigham and Women's Hospital, Boston, MA, USA.  

Reference: Int J Comput Assist Radiol Surg. 2015 Apr 7. Epub ahead of print.
doi: 10.1007/s11548-015-1180-7


PubMed Abstract
PMID: 25847666

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