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Li L, Wu F, Wang S, Luo X, Martín-Isla C, Zhai S, Zhang J, Liu Y, Zhang Z, Ankenbrand MJ, Jiang H, Zhang X, Wang L, Arega TW, Altunok E, Zhao Z, Li F, Ma J, Yang X, Puybareau E, Oksuz I, Bricq S, Li W, Punithakumar K, Tsaftaris SA, Schreiber LM, Yang M, Liu G, Xia Y, Wang G, Escalera S, Zhuang X. MyoPS: A benchmark of myocardial pathology segmentation combining three-sequence cardiac magnetic resonance images. Med Image Anal 2023; 87:102808. [PMID: 37087838 DOI: 10.1016/j.media.2023.102808] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 01/11/2023] [Accepted: 03/30/2023] [Indexed: 04/07/2023]
Abstract
Assessment of myocardial viability is essential in diagnosis and treatment management of patients suffering from myocardial infarction, and classification of pathology on the myocardium is the key to this assessment. This work defines a new task of medical image analysis, i.e., to perform myocardial pathology segmentation (MyoPS) combining three-sequence cardiac magnetic resonance (CMR) images, which was first proposed in the MyoPS challenge, in conjunction with MICCAI 2020. Note that MyoPS refers to both myocardial pathology segmentation and the challenge in this paper. The challenge provided 45 paired and pre-aligned CMR images, allowing algorithms to combine the complementary information from the three CMR sequences for pathology segmentation. In this article, we provide details of the challenge, survey the works from fifteen participants and interpret their methods according to five aspects, i.e., preprocessing, data augmentation, learning strategy, model architecture and post-processing. In addition, we analyze the results with respect to different factors, in order to examine the key obstacles and explore the potential of solutions, as well as to provide a benchmark for future research. The average Dice scores of submitted algorithms were 0.614±0.231 and 0.644±0.153 for myocardial scars and edema, respectively. We conclude that while promising results have been reported, the research is still in the early stage, and more in-depth exploration is needed before a successful application to the clinics. MyoPS data and evaluation tool continue to be publicly available upon registration via its homepage (www.sdspeople.fudan.edu.cn/zhuangxiahai/0/myops20/).
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Affiliation(s)
- Lei Li
- School of Data Science, Fudan University, Shanghai, China; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
| | - Fuping Wu
- School of Data Science, Fudan University, Shanghai, China.
| | - Sihan Wang
- School of Data Science, Fudan University, Shanghai, China.
| | - Xinzhe Luo
- School of Data Science, Fudan University, Shanghai, China
| | - Carlos Martín-Isla
- Departament de Matemàtiques & Informàtica, Universitat de Barcelona, Barcelona, Spain
| | - Shuwei Zhai
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Jianpeng Zhang
- School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China
| | - Yanfei Liu
- College of Electrical and Information Engineering, Hunan University, Changsha, China
| | - Zhen Zhang
- College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
| | - Markus J Ankenbrand
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center, Wuerzburg University Hospitals, Wuerzburg, Germany
| | - Haochuan Jiang
- School of Engineering, University of Edinburgh, Edinburgh, UK; School of Robotics, Xi'an Jiaotong-Liverpool University, Suzhou, China
| | - Xiaoran Zhang
- Department of Electrical and Computer Engineering, University of California, LA, USA
| | - Linhong Wang
- Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China
| | | | - Elif Altunok
- Computer Engineering Department, Istanbul Technical University, Istanbul, Turkey
| | - Zhou Zhao
- EPITA Research and Development Laboratory (LRDE), Le Kremlin-Bicêtre, France
| | - Feiyan Li
- Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Jun Ma
- Department of Mathematics, Nanjing University of Science and Technology, Nanjing, China
| | - Xiaoping Yang
- Department of Mathematics, Nanjing University, Nanjing, China
| | - Elodie Puybareau
- EPITA Research and Development Laboratory (LRDE), Le Kremlin-Bicêtre, France
| | - Ilkay Oksuz
- Computer Engineering Department, Istanbul Technical University, Istanbul, Turkey
| | - Stephanie Bricq
- ImViA Laboratory, Université Bourgogne Franche-Comté, Dijon, France
| | - Weisheng Li
- Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China
| | | | | | - Laura M Schreiber
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center, Wuerzburg University Hospitals, Wuerzburg, Germany
| | - Mingjing Yang
- College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
| | - Guocai Liu
- College of Electrical and Information Engineering, Hunan University, Changsha, China; National Engineering Laboratory for Robot Visual Perception and Control Technology, Changsha, China
| | - Yong Xia
- School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China
| | - Guotai Wang
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Sergio Escalera
- Departament de Matemàtiques & Informàtica, Universitat de Barcelona, Barcelona, Spain; Computer Vision Center, Universitat Autònoma de Barcelona, Spain
| | - Xiahai Zhuang
- School of Data Science, Fudan University, Shanghai, China.
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Wang KN, Yang X, Miao J, Li L, Yao J, Zhou P, Xue W, Zhou GQ, Zhuang X, Ni D. AWSnet: An Auto-weighted Supervision Attention Network for Myocardial Scar and Edema Segmentation in Multi-sequence Cardiac Magnetic Resonance Images. Med Image Anal 2022; 77:102362. [DOI: 10.1016/j.media.2022.102362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 10/26/2021] [Accepted: 01/10/2022] [Indexed: 10/19/2022]
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Tufvesson J, Carlsson M, Aletras AH, Engblom H, Deux JF, Koul S, Sörensson P, Pernow J, Atar D, Erlinge D, Arheden H, Heiberg E. Automatic segmentation of myocardium at risk from contrast enhanced SSFP CMR: validation against expert readers and SPECT. BMC Med Imaging 2016; 16:19. [PMID: 26946139 PMCID: PMC4779553 DOI: 10.1186/s12880-016-0124-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Accepted: 02/24/2016] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND Efficacy of reperfusion therapy can be assessed as myocardial salvage index (MSI) by determining the size of myocardium at risk (MaR) and myocardial infarction (MI), (MSI = 1-MI/MaR). Cardiovascular magnetic resonance (CMR) can be used to assess MI by late gadolinium enhancement (LGE) and MaR by either T2-weighted imaging or contrast enhanced SSFP (CE-SSFP). Automatic segmentation algorithms have been developed and validated for MI by LGE as well as for MaR by T2-weighted imaging. There are, however, no algorithms available for CE-SSFP. Therefore, the aim of this study was to develop and validate automatic segmentation of MaR in CE-SSFP. METHODS The automatic algorithm applies surface coil intensity correction and classifies myocardial intensities by Expectation Maximization to define a MaR region based on a priori regional criteria, and infarct region from LGE. Automatic segmentation was validated against manual delineation by expert readers in 183 patients with reperfused acute MI from two multi-center randomized clinical trials (RCT) (CHILL-MI and MITOCARE) and against myocardial perfusion SPECT in an additional set (n = 16). Endocardial and epicardial borders were manually delineated at end-diastole and end-systole. Manual delineation of MaR was used as reference and inter-observer variability was assessed for both manual delineation and automatic segmentation of MaR in a subset of patients (n = 15). MaR was expressed as percent of left ventricular mass (%LVM) and analyzed by bias (mean ± standard deviation). Regional agreement was analyzed by Dice Similarity Coefficient (DSC) (mean ± standard deviation). RESULTS MaR assessed by manual and automatic segmentation were 36 ± 10% and 37 ± 11%LVM respectively with bias 1 ± 6%LVM and regional agreement DSC 0.85 ± 0.08 (n = 183). MaR assessed by SPECT and CE-SSFP automatic segmentation were 27 ± 10%LVM and 29 ± 7%LVM respectively with bias 2 ± 7%LVM. Inter-observer variability was 0 ± 3%LVM for manual delineation and -1 ± 2%LVM for automatic segmentation. CONCLUSIONS Automatic segmentation of MaR in CE-SSFP was validated against manual delineation in multi-center, multi-vendor studies with low bias and high regional agreement. Bias and variability was similar to inter-observer variability of manual delineation and inter-observer variability was decreased by automatic segmentation. Thus, the proposed automatic segmentation can be used to reduce subjectivity in quantification of MaR in RCT. CLINICAL TRIAL REGISTRATION NCT01379261. NCT01374321.
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Affiliation(s)
- Jane Tufvesson
- Department of Clinical Physiology, Skåne University Hospital in Lund, Lund University, Lund, Sweden.
- Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Sweden.
| | - Marcus Carlsson
- Department of Clinical Physiology, Skåne University Hospital in Lund, Lund University, Lund, Sweden.
| | - Anthony H Aletras
- Department of Clinical Physiology, Skåne University Hospital in Lund, Lund University, Lund, Sweden.
- Laboratory of Medical Informatics, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.
| | - Henrik Engblom
- Department of Clinical Physiology, Skåne University Hospital in Lund, Lund University, Lund, Sweden.
| | | | - Sasha Koul
- Department of Cardiology, Lund University, Lund, Sweden.
| | - Peder Sörensson
- Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
| | - John Pernow
- Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
| | - Dan Atar
- Department of Cardiology B, Oslo, University Hospital Ullevål and Faculty of Medicine, University of Oslo, Oslo, Norway.
| | - David Erlinge
- Department of Cardiology, Lund University, Lund, Sweden.
| | - Håkan Arheden
- Department of Clinical Physiology, Skåne University Hospital in Lund, Lund University, Lund, Sweden.
| | - Einar Heiberg
- Department of Clinical Physiology, Skåne University Hospital in Lund, Lund University, Lund, Sweden.
- Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Sweden.
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Pennell DJ, Baksi AJ, Prasad SK, Raphael CE, Kilner PJ, Mohiaddin RH, Alpendurada F, Babu-Narayan SV, Schneider J, Firmin DN. Review of Journal of Cardiovascular Magnetic Resonance 2014. J Cardiovasc Magn Reson 2015; 17:99. [PMID: 26589839 PMCID: PMC4654908 DOI: 10.1186/s12968-015-0203-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Accepted: 11/08/2015] [Indexed: 01/19/2023] Open
Abstract
There were 102 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2014, which is a 6% decrease on the 109 articles published in 2013. The quality of the submissions continues to increase. The 2013 JCMR Impact Factor (which is published in June 2014) fell to 4.72 from 5.11 for 2012 (as published in June 2013). The 2013 impact factor means that the JCMR papers that were published in 2011 and 2012 were cited on average 4.72 times in 2013. The impact factor undergoes natural variation according to citation rates of papers in the 2 years following publication, and is significantly influenced by highly cited papers such as official reports. However, the progress of the journal's impact over the last 5 years has been impressive. Our acceptance rate is <25% and has been falling because the number of articles being submitted has been increasing. In accordance with Open-Access publishing, the JCMR articles go on-line as they are accepted with no collating of the articles into sections or special thematic issues. For this reason, the Editors have felt that it is useful once per calendar year to summarize the papers for the readership into broad areas of interest or theme, so that areas of interest can be reviewed in a single article in relation to each other and other recent JCMR articles. The papers are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought in the journal. We hope that you find the open-access system increases wider reading and citation of your papers, and that you will continue to send your quality papers to JCMR for publication.
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Affiliation(s)
- D J Pennell
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - A J Baksi
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - S K Prasad
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - C E Raphael
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - P J Kilner
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - R H Mohiaddin
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - F Alpendurada
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - S V Babu-Narayan
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - J Schneider
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - D N Firmin
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
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5
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Khan JN, Nazir SA, Horsfield MA, Singh A, Kanagala P, Greenwood JP, Gershlick AH, McCann GP. Comparison of semi-automated methods to quantify infarct size and area at risk by cardiovascular magnetic resonance imaging at 1.5T and 3.0T field strengths. BMC Res Notes 2015; 8:52. [PMID: 25889795 PMCID: PMC4347654 DOI: 10.1186/s13104-015-1007-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2014] [Accepted: 02/09/2015] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND There is currently no gold standard technique for quantifying infarct size (IS) and ischaemic area-at-risk (AAR [oedema]) on late gadolinium enhancement imaging (LGE) and T2-weighted short tau inversion recovery imaging (T2w-STIR) respectively. This study aimed to compare the accuracy and reproducibility of IS and AAR quantification on LGE and T2w-STIR imaging using Otsu's Automated Technique (OAT) with currently used methods at 1.5T and 3.0T post acute ST-segment elevation myocardial infarction (STEMI). METHODS Ten patients were assessed at 1.5T and 10 at 3.0T. IS was assessed on LGE using 5-8 standard-deviation thresholding (5-8SD), full-width half-maximum (FWHM) quantification and OAT. AAR was assessed on T2w-STIR using 2SD and OAT. Accuracy was assessed by comparison with manual quantification. Interobserver and intraobserver variabilities were assessed using Intraclass Correlation Coefficients and Bland-Altman analysis. IS using each technique was correlated with left ventricular ejection fraction (LVEF). RESULTS FWHM and 8SD-derived IS closely correlated with manual assessment at both field strengths (1.5T: 18.3 ± 10.7% LV Mass [LVM] with FWHM, 17.7 ± 14.4% LVM with 8SD, 16.5 ± 10.3% LVM with manual quantification; 3.0T: 10.8 ± 8.2% LVM with FWHM, 11.4 ± 9.0% LVM with 8SD, 11.5 ± 9.0% LVM with manual quantification). 5SD and OAT overestimated IS at both field strengths. OAT, 2SD and manually quantified AAR closely correlated at 1.5T, but OAT overestimated AAR compared with manual assessment at 3.0T. IS and AAR derived by FWHM and OAT respectively had better reproducibility compared with manual and SD-based quantification. FWHM IS correlated strongest with LVEF. CONCLUSIONS FWHM quantification of IS is accurate, reproducible and correlates strongly with LVEF, whereas 5SD and OAT overestimate IS. OAT accurately assesses AAR at 1.5T and with excellent reproducibility. OAT overestimated AAR at 3.0T and thus cannot be recommended as the preferred method for AAR quantification at 3.0T.
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Affiliation(s)
- Jamal N Khan
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Groby Road, LE3 9QP, Leicester, UK.
| | - Sheraz A Nazir
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Groby Road, LE3 9QP, Leicester, UK.
| | - Mark A Horsfield
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Groby Road, LE3 9QP, Leicester, UK.
| | - Anvesha Singh
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Groby Road, LE3 9QP, Leicester, UK.
| | - Prathap Kanagala
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Groby Road, LE3 9QP, Leicester, UK.
| | - John P Greenwood
- Division of Cardiovascular and Diabetes Research, Leeds Institute of Genetics, Health and Therapeutics, University of Leeds, LS2 9JT, Leeds, UK.
| | - Anthony H Gershlick
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Groby Road, LE3 9QP, Leicester, UK.
| | - Gerry P McCann
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Groby Road, LE3 9QP, Leicester, UK.
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Pennell DJ, Baksi AJ, Kilner PJ, Mohiaddin RH, Prasad SK, Alpendurada F, Babu-Narayan SV, Neubauer S, Firmin DN. Review of Journal of Cardiovascular Magnetic Resonance 2013. J Cardiovasc Magn Reson 2014; 16:100. [PMID: 25475898 PMCID: PMC4256918 DOI: 10.1186/s12968-014-0100-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2014] [Accepted: 11/21/2014] [Indexed: 01/19/2023] Open
Abstract
There were 109 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2013, which is a 21% increase on the 90 articles published in 2012. The quality of the submissions continues to increase. The editors are delighted to report that the 2012 JCMR Impact Factor (which is published in June 2013) has risen to 5.11, up from 4.44 for 2011 (as published in June 2012), a 15% increase and taking us through the 5 threshold for the first time. The 2012 impact factor means that the JCMR papers that were published in 2010 and 2011 were cited on average 5.11 times in 2012. The impact factor undergoes natural variation according to citation rates of papers in the 2 years following publication, and is significantly influenced by highly cited papers such as official reports. However, the progress of the journal's impact over the last 5 years has been impressive. Our acceptance rate is <25% and has been falling because the number of articles being submitted has been increasing. In accordance with Open-Access publishing, the JCMR articles go on-line as they are accepted with no collating of the articles into sections or special thematic issues. For this reason, the Editors have felt that it is useful once per calendar year to summarize the papers for the readership into broad areas of interest or theme, so that areas of interest can be reviewed in a single article in relation to each other and other recent JCMR articles. The papers are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought in the journal. We hope that you find the open-access system increases wider reading and citation of your papers, and that you will continue to send your quality manuscripts to JCMR for publication.
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Affiliation(s)
- Dudley John Pennell
- />Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP UK
- />Imperial College, London, UK
| | - Arun John Baksi
- />Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP UK
- />Imperial College, London, UK
| | - Philip John Kilner
- />Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP UK
- />Imperial College, London, UK
| | - Raad Hashem Mohiaddin
- />Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP UK
- />Imperial College, London, UK
| | - Sanjay Kumar Prasad
- />Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP UK
- />Imperial College, London, UK
| | - Francisco Alpendurada
- />Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP UK
- />Imperial College, London, UK
| | - Sonya Vidya Babu-Narayan
- />Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP UK
- />Imperial College, London, UK
| | | | - David Nigel Firmin
- />Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP UK
- />Imperial College, London, UK
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7
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White SK, Flett AS, Moon JC. Automated scar quantification by CMR: a step in the right direction. J Thorac Dis 2013; 5:381-2. [PMID: 23991290 DOI: 10.3978/j.issn.2072-1439.2013.07.22] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2013] [Accepted: 07/09/2013] [Indexed: 11/14/2022]
Affiliation(s)
- Steven K White
- The Heart Hospital, London W1G 8PH, UK; ; Institute of Cardiovascular Science, University College London, London, WC1E 6BT, UK
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