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MRI-TRUS Image Synthesis with Application to Image-Guided Prostate Intervention

Onofrey, John A. and Oksuz, Ilkay and Sarkar, Saradwata and Venkataraman, Rajesh and Staib, Lawrence H. and Papademetris, Xenophon MRI-TRUS Image Synthesis with Application to Image-Guided Prostate Intervention. In: Simulation and Synthesis in Medical Imaging. First International Workshop, SASHIMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings. Lecture Notes in Computer Science (9968). Springer International Publishing, pp. 157-166. ISBN 978-3-319-46630-9 (2016)

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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 surface-based 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.

Item Type: Book Section
Projects: Grant R41/42-CA186414
Funders: NIH
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RZ Other systems of medicine
T Technology > T Technology (General)
Research Area: Computer Science and Applications
Depositing User: Caterina Tangheroni
Date Deposited: 01 Feb 2017 08:36
Last Modified: 01 Feb 2017 08:36
URI: http://eprints.imtlucca.it/id/eprint/3651

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