MRI-TRUS image synthesis with application to image-guided prostate intervention

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Abstract

Accurate and robust fusion of pre-procedure magnetic resonance imaging (MRI) to intra-procedure trans-rectal ultrasound (TRUS) imaging is necessary for image-guided prostate cancer biopsy procedures. The current clinical standard for image fusion relies on non-rigid surfacebased registration between semi-automatically segmented prostate surfaces in both the MRI and TRUS. This surface-based registration method does not take advantage of internal anatomical prostate structures, which have the potential to provide useful information for image registration. However, non-rigid, multi-modal intensity-based MRI-TRUS registration is challenging due to highly non-linear intensities relationships between MRI and TRUS. In this paper, we present preliminary work using image synthesis to cast this problem into a mono-modal registration task by using a large database of over 100 clinical MRI-TRUS image pairs to learn a joint model of MR-TRUS appearance. Thus, given an MRI, we use this learned joint appearance model to synthesize the patient’s corresponding TRUS image appearance with which we could potentially perform mono-modal intensity-based registration. We present preliminary results of this approach.

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Onofrey, J. A., Oksuz, I., Sarkar, S., Venkataraman, R., Staib, L. H., & Papademetris, X. (2016). MRI-TRUS image synthesis with application to image-guided prostate intervention. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9968 LNCS, pp. 157–166). Springer Verlag. https://doi.org/10.1007/978-3-319-46630-9_16

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