Precise ultrasound bone registration with learning-based segmentation and speed of sound calibration
Salehi M, Prevost R, Moctezuma JL, Navab N, Wein W (2017)
Publication Type: Conference contribution
Publication year: 2017
Journal
Publisher: Springer Verlag
Book Volume: 10434 LNCS
Pages Range: 682-690
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Quebec City, QC, CAN
ISBN: 9783319661841
DOI: 10.1007/978-3-319-66185-8_77
Abstract
Ultrasound imaging is increasingly used in navigated surgery and registration-based applications. However, spatial information quality in ultrasound is relatively inferior to other modalities. Main limiting factors for an accurate registration between ultrasound and other modalities are tissue deformation and speed of sound variation throughout the body. The bone surface in ultrasound is a landmark which is less affected by such geometric distortions. In this paper, we present a workflow to accurately register intra-operative ultrasound images to a reference pre-operative CT volume based on an automatic and real-time image processing pipeline. We show that a convolutional neural network is able to produce robust, accurate and fast bone segmentation of such ultrasound images. We also develop a dedicated method to perform online speed of sound calibration by focusing on the bone area and optimizing the appearance of steered compounded images. We provide extensive validation on both phantom and real cadaver data obtaining overall errors under one millimeter.
Involved external institutions
ImFusion GmbH
Germany (DE)
Stryker Leibinger GmbH & Co. KG
Germany (DE)
Technische Universität München (TUM)
Germany (DE)
Germany (DE)
Stryker Leibinger GmbH & Co. KG
Germany (DE)
Technische Universität München (TUM)
Germany (DE)
How to cite
APA:
Salehi, M., Prevost, R., Moctezuma, J.L., Navab, N., & Wein, W. (2017). Precise ultrasound bone registration with learning-based segmentation and speed of sound calibration. In Pierre Jannin, Simon Duchesne, Maxime Descoteaux, Alfred Franz, D. Louis Collins, Lena Maier-Hein (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 682-690). Quebec City, QC, CAN: Springer Verlag.
MLA:
Salehi, Mehrdad, et al. "Precise ultrasound bone registration with learning-based segmentation and speed of sound calibration." Proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, Quebec City, QC, CAN Ed. Pierre Jannin, Simon Duchesne, Maxime Descoteaux, Alfred Franz, D. Louis Collins, Lena Maier-Hein, Springer Verlag, 2017. 682-690.
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