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Proceedings Paper

Transformation optimization and image blending for 3D liver ultrasound series stitching
Author(s): Yuanyuan Sun; Taygun Kekec; Adriaan Moelker; Wiro J. Niessen; Theo van Walsum
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Paper Abstract

We propose a consistent ultrasound volume stitching framework, with the intention to produce a volume with higher image quality and extended field-of-view in this work. Directly using pair-wise registrations for stitching may lead to geometric errors. Therefore, we propose an approach to improve the image alignment by optimizing a consistency metric over multiple pairwise registrations. In the optimization, we utilize transformed points to effectively compute a distance between rigid transformations. The method has been evaluated on synthetic, phantom and clinical data. The results indicate that our transformation optimization method is effective and our stitching framework has a good geometric precision. Also, the compound images have been demonstrated to have improved CNR values.

Paper Details

Date Published: 16 March 2020
PDF: 7 pages
Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 1131512 (16 March 2020);
Show Author Affiliations
Yuanyuan Sun, Erasmus MC (Netherlands)
Taygun Kekec, Erasmus MC (Netherlands)
Adriaan Moelker, Erasmus MC (Netherlands)
Wiro J. Niessen, Erasmus MC (Netherlands)
Delft Univ. of Technology (Netherlands)
Theo van Walsum, Erasmus MC (Netherlands)

Published in SPIE Proceedings Vol. 11315:
Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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