{"id":12320,"date":"2024-03-05T10:28:52","date_gmt":"2024-03-05T07:28:52","guid":{"rendered":"https:\/\/umram.bilkent.edu.tr\/?p=12320"},"modified":"2024-03-05T10:28:52","modified_gmt":"2024-03-05T07:28:52","slug":"umram-nsc-asbam-fall-2023-seminars-enhancing-mri-performance-through-computational-imaging","status":"publish","type":"post","link":"https:\/\/umram.bilkent.edu.tr\/index.php\/2024\/03\/05\/umram-nsc-asbam-fall-2023-seminars-enhancing-mri-performance-through-computational-imaging\/","title":{"rendered":"UMRAM\/NSC-ASBAM Fall 2023 Seminars: ”Enhancing MRI Performance through Computational Imaging”"},"content":{"rendered":"

\nMariya Doneva, Ph.D.
\n<\/strong>Philips Research, Germany<\/p>\n

Date\/Time:<\/strong>\u00a0Thursday, Nov 23rd, 2023, at 17:30PM
\nZoom Link:<\/strong>\u00a0https:\/\/zoom.us\/j\/98924400569<\/a><\/p>\n

Abstract:<\/strong>\u00a0Over the past two decades, the significance of MR image reconstruction has tremendously increased, enabling reduced scan time, improved image quality, and extraction of additional information from the measured data. During this period, MRI has witnessed extensive developments in advanced computational algorithms for image reconstruction, many of which have been fueled by signal processing advances in several areas, including multi-channel sampling, compressed sensing, dictionary learning, low-rank and structured low-rank methods. Recently, also neural networks have been employed for image reconstruction achieving further improvements in scan time and image quality. Most importantly, some of these techniques have found their way in the products of MRI vendors and show significant impact in clinical practice. These developments, together with the advancements in computational hardware have opened a new research field of MRI reconstruction as a computational imaging problem. In this talk, I will discuss the framework of MRI reconstruction as a computational imaging problem and the advantages it provides in enhancing the MR performance thereby addressing important clinical needs.<\/p>\n

Bio:<\/strong>\u00a0Dr. Doneva is a Senior Scientist and a Team Lead at Philips\u00a0Research, Hamburg, Germany, which she joined in 2010. She received her BSc and MSc degrees in Physics from the\u00a0University of Oldenburg in 2006 and 2007, respectively and her PhD degree in Physics from the University of L\u00fcbeck in 2010.\u00a0She was a Research Associate at Electrical Engineering and
\nComputer Sciences Department at UC Berkeley between 2015\u00a0and 2016. Her work has yielded many innovations related to\u00a0imaging workflow improvements, novel quantitative MRI\u00a0approaches, and most prominently fast MRI data acquisition based on compressed sensing allowing significant reduction of the scan time of routine clinical scans, which has been already integrated in the clinical routine of many hospitals and used to scan\u00a0millions of patients. She has been granted over 30 patents for her work in MR\u00a0imaging.<\/p>\n

\nDr. Doneva was an Organizing Committee Member of multiple conferences including the International Society for Magnetic Resonance in Medicine (ISMRM) (2019-2021),\u00a0IEEE International Symposium on Biomedical Imaging (ISBI) (2020), the ISMRM\u00a0Workshop on Data Sampling and Image Reconstruction (2020), and the SIAM\u00a0Conference on Imaging Science 2022.\u00a0She was Guest Editor, IEEE Signal Processing Magazine Special Issue on Computational MRI: Compressive Sensing and Beyond; Editor, comprehensive\u00a0reference book on Quantitative Magnetic Resonance Imaging; Editorial Board\u00a0Member, Magnetic Resonance in Medicine and IEEE Transactions on Computational\u00a0Imaging; and Editor of a reference book on MR image reconstruction.\u00a0Dr. Doneva\u2019s research interests include methods for efficient data acquisition, image\u00a0reconstruction and quantitative parameter mapping in the context of magnetic resonance imaging. Her work involves developing mathematical optimization and\u00a0signal processing approaches that aim at improving the MR scan efficiency and obtaining robust and reliable (multi-parametric) quantitative information for\u00a0diagnostics and therapy follow up.<\/p>\n","protected":false},"excerpt":{"rendered":"

Mariya Doneva, Ph.D. Philips Research, Germany Date\/Time:\u00a0Thursday, Nov 23rd, 2023, at 17:30PM Zoom Link:\u00a0https:\/\/zoom.us\/j\/98924400569 Abstract:\u00a0Over the past two decades, the significance of MR image reconstruction has tremendously increased, enabling reduced scan time, improved image quality, and extraction of additional information from the measured data. During this period, MRI has witnessed extensive developments in advanced computational […]<\/p>\n","protected":false},"author":7,"featured_media":12280,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[746],"tags":[],"_links":{"self":[{"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/posts\/12320"}],"collection":[{"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/comments?post=12320"}],"version-history":[{"count":1,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/posts\/12320\/revisions"}],"predecessor-version":[{"id":12321,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/posts\/12320\/revisions\/12321"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/media\/12280"}],"wp:attachment":[{"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/media?parent=12320"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/categories?post=12320"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/tags?post=12320"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}