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

John A. Onofrey; Ilkay Oksuz; Saradwata Sarkar; Rajesh Venkataraman; Lawrence H. Staib; Xenophon Papademetris

doi:10.1007/978-3-319-46630-9_16

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

John A. Onofrey^*, Ilkay Oksuz, Saradwata Sarkar, Rajesh Venkataraman, Lawrence H. Staib, Xenophon Papademetris

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

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.

Original language	English
Title of host publication	Simulation and Synthesis in Medical Imaging - 1st International Workshop, SASHIMI 2016 held in conjunction with MICCAI 2016, Proceedings
Editors	Sotirios A. Tsaftaris, Ali Gooya, Alejandro F. Frangi, Jerry L. Prince
Publisher	Springer Verlag
Pages	157-166
Number of pages	10
ISBN (Print)	9783319466293
DOIs	https://doi.org/10.1007/978-3-319-46630-9_16
Publication status	Published - 2016
Externally published	Yes
Event	1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece Duration: 21 Oct 2016 → 21 Oct 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9968 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Country/Territory	Greece
City	Athens
Period	21/10/16 → 21/10/16

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2016.

Funding

This work was supported in part by the NIH under grant R41/42-CA186414.

Funders	Funder number
National Institutes of Health	R41/42-CA186414

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-319-46630-9_16

Cite this

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 S. A. Tsaftaris, A. Gooya, A. F. Frangi, & J. L. Prince (Eds.), Simulation and Synthesis in Medical Imaging - 1st International Workshop, SASHIMI 2016 held in conjunction with MICCAI 2016, Proceedings (pp. 157-166). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9968 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46630-9_16

Onofrey, John A. ; Oksuz, Ilkay ; Sarkar, Saradwata et al. / MRI-TRUS image synthesis with application to image-guided prostate intervention. Simulation and Synthesis in Medical Imaging - 1st International Workshop, SASHIMI 2016 held in conjunction with MICCAI 2016, Proceedings. editor / Sotirios A. Tsaftaris ; Ali Gooya ; Alejandro F. Frangi ; Jerry L. Prince. Springer Verlag, 2016. pp. 157-166 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "MRI-TRUS image synthesis with application to image-guided prostate intervention",

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{\textquoteright}s corresponding TRUS image appearance with which we could potentially perform mono-modal intensity-based registration. We present preliminary results of this approach.",

author = "Onofrey, {John A.} and Ilkay Oksuz and Saradwata Sarkar and Rajesh Venkataraman and Staib, {Lawrence H.} and Xenophon Papademetris",

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Onofrey, JA, Oksuz, I, Sarkar, S, Venkataraman, R, Staib, LH & Papademetris, X 2016, MRI-TRUS image synthesis with application to image-guided prostate intervention. in SA Tsaftaris, A Gooya, AF Frangi & JL Prince (eds), Simulation and Synthesis in Medical Imaging - 1st International Workshop, SASHIMI 2016 held in conjunction with MICCAI 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9968 LNCS, Springer Verlag, pp. 157-166, 1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, Athens, Greece, 21/10/16. https://doi.org/10.1007/978-3-319-46630-9_16

MRI-TRUS image synthesis with application to image-guided prostate intervention. / Onofrey, John A.; Oksuz, Ilkay; Sarkar, Saradwata et al.
Simulation and Synthesis in Medical Imaging - 1st International Workshop, SASHIMI 2016 held in conjunction with MICCAI 2016, Proceedings. ed. / Sotirios A. Tsaftaris; Ali Gooya; Alejandro F. Frangi; Jerry L. Prince. Springer Verlag, 2016. p. 157-166 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9968 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Oksuz, Ilkay

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AU - Staib, Lawrence H.

AU - Papademetris, Xenophon

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AB - 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 JA, Oksuz I, Sarkar S, Venkataraman R, Staib LH, Papademetris X. MRI-TRUS image synthesis with application to image-guided prostate intervention. In Tsaftaris SA, Gooya A, Frangi AF, Prince JL, editors, Simulation and Synthesis in Medical Imaging - 1st International Workshop, SASHIMI 2016 held in conjunction with MICCAI 2016, Proceedings. Springer Verlag. 2016. p. 157-166. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46630-9_16

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

Abstract

Publication series

Conference

Bibliographical note

Funding

UN SDGs

Access to Document

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