{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pvr-patch-to-volume-reconstruction-for-large","title":"PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI","arxiv_id":"1611.07289","date":"2016-11-22","proceeding":null,"authors":["Amir Alansary","Bernhard Kainz","Martin Rajchl","Maria Murgasova","Mellisa Damodaram","David F. A. Lloyd","Alice Davidson","Steven G. McDonagh","Mary Rutherford","Joseph V. Hajnal","Daniel Rueckert"],"abstract":"In this paper we present a novel method for the correction of motion\nartifacts that are present in fetal Magnetic Resonance Imaging (MRI) scans of\nthe whole uterus. Contrary to current slice-to-volume registration (SVR)\nmethods, requiring an inflexible anatomical enclosure of a single investigated\norgan, the proposed patch-to-volume reconstruction (PVR) approach is able to\nreconstruct a large field of view of non-rigidly deforming structures. It\nrelaxes rigid motion assumptions by introducing a specific amount of redundant\ninformation that is exploited with parallelized patch-wise optimization,\nsuper-resolution, and automatic outlier rejection. We further describe and\nprovide an efficient parallel implementation of PVR allowing its execution\nwithin reasonable time on commercially available graphics processing units\n(GPU), enabling its use in the clinical practice. We evaluate PVR's\ncomputational overhead compared to standard methods and observe improved\nreconstruction accuracy in presence of affine motion artifacts of approximately\n30% compared to conventional SVR in synthetic experiments. Furthermore, we have\nevaluated our method qualitatively and quantitatively on real fetal MRI data\nsubject to maternal breathing and sudden fetal movements. We evaluate\npeak-signal-to-noise ratio (PSNR), structural similarity index (SSIM), and\ncross correlation (CC) with respect to the originally acquired data and provide\na method for visual inspection of reconstruction uncertainty. With these\nexperiments we demonstrate successful application of PVR motion compensation to\nthe whole uterus, the human fetus, and the human placenta.","url_abs":"http://arxiv.org/abs/1611.07289v2","url_pdf":"http://arxiv.org/pdf/1611.07289v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"pvr-patch-to-volume-reconstruction-for-large","repo_url":"https://github.com/bkainz/fetalReconstruction","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":null,"task_name":"GPU"},{"task_slug":"motion-compensation","task_name":"Motion Compensation"},{"task_slug":"ssim","task_name":"SSIM"},{"task_slug":"super-resolution","task_name":"Super-Resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}