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Point-Spread-Function-Aware Slice-to-Volume Registration: Application to Upper Abdominal MRI Super-Resolution: Application to upper abdominal MRI super-resolution

Research output: Chapter in Book/Report/Conference proceedingConference paper

Michael Ebner, Manil Chouhan, Premal A. Patel, David Atkinson, Zahir Amin, Samantha Read, Shonit Punwani, Stuart Taylor, Tom Vercauteren, Sébastien Ourselin

Original languageEnglish
Title of host publicationReconstruction, Segmentation, and Analysis of Medical Images - 1st International Workshops, RAMBO 2016 and HVSMR 2016 Held in Conjunction with MICCAI 2016, Revised Selected Papers
PublisherSpringer Verlag
Pages3-13
Number of pages11
Volume10129
ISBN (Print)9783319522791
DOIs
Publication statusE-pub ahead of print - 19 Jan 2017
Event1st International Workshops on Reconstruction and Analysis of Moving Body Organs, RAMBO 2016 and 1st International Workshops on Whole-Heart and Great Vessel Segmentation from 3D Cardiovascular MRI in Congenital Heart Disease, HVSMR 2016 Held in Conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece
Duration: 17 Oct 201621 Oct 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10129 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Workshops on Reconstruction and Analysis of Moving Body Organs, RAMBO 2016 and 1st International Workshops on Whole-Heart and Great Vessel Segmentation from 3D Cardiovascular MRI in Congenital Heart Disease, HVSMR 2016 Held in Conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
CountryGreece
CityAthens
Period17/10/201621/10/2016

King's Authors

Abstract

MR image acquisition of moving organs remains challenging despite the advances in ultra-fast 2D MRI sequences. Post-acquisition techniques have been proposed to increase spatial resolution a posteriori by combining acquired orthogonal stacks into a single, high-resolution (HR) volume. Current super-resolution techniques classically rely on a two-step procedure. The volumetric reconstruction step leverages a physical slice acquisition model. However, the motion correction step typically neglects the point spread function (PSF) information. In this paper, we propose a PSF-aware slice-to-volume registration approach and, for the first time, demonstrate the potential benefit of Super-Resolution for upper abdominal imaging. Our novel reconstruction pipeline takes advantage of different MR acquisitions clinically used in routine MR cholangio-pancreatography studies to guide the registration. On evaluation of clinically relevant image information, our approach outperforms state-of-the-art reconstruction toolkits in terms of visual clarity and preservation of raw data information. Overall, we achieve promising results towards replacing currently required CT scans.

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