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Articles published in
Eur J Radiol
    February 2024
  1. FOOLADI M, Soleymani Y, Rahmim A, Farzanefar S, et al
    Impact of different reconstruction algorithms and setting parameters on radiomics features of PSMA PET images: A preliminary study.
    Eur J Radiol. 2024;172:111349.
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    November 2023
  2. LI S, Liu J, Wang G, Feng L, et al
    Predictive value of 2-deoxy-2-fluorine-18-fluoro-D-glucose positron emission tomography/computed tomography parameters for MYCN amplification in high-risk neuroblastoma.
    Eur J Radiol. 2023;170:111243.
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    October 2023
  3. CHAMPENDAL M, Muller H, Prior JO, Dos Reis CS, et al
    A scoping review of interpretability and explainability concerning artificial intelligence methods in medical imaging.
    Eur J Radiol. 2023;169:111159.
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    September 2023
  4. MICHALOPOULOU E, Pugalenthi PP, Darker I, Chen Y, et al
    A comparison of breast screening performance based on a standardised test, during and outside of the COVID-19 lockdown period.
    Eur J Radiol. 2023;168:111117.
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    June 2023
  5. ZHANG KS, Neelsen CJO, Wennmann M, Glemser PA, et al
    Same-day repeatability and Between-Sequence reproducibility of Mean ADC in PI-RADS lesions.
    Eur J Radiol. 2023;165:110898.
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    May 2023
  6. STEINBERG HL, Auer T, Gebauer B, Kloeckner R, et al
    Embolization of active arterial bleeding in COVID-19 patients: A multicenter study.
    Eur J Radiol. 2023;165:110892.
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  7. YOO SJ, Kim H, Witanto JN, Inui S, et al
    Generative adversarial network for automatic quantification of Coronavirus disease 2019 pneumonia on chest radiographs.
    Eur J Radiol. 2023;164:110858.
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  8. KOEPPEL DR, Boehm IB
    Shortage of iodinated contrast media: Status and possible chances - A systematic review.
    Eur J Radiol. 2023;164:110853.
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    April 2023
  9. MONTI CB, Zanardo M, Capra D, Folco G, et al
    Myocardial extracellular volume assessment at CT in hospitalized COVID-19 patients with regards to pulmonary embolism.
    Eur J Radiol. 2023;163:110809.
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  10. KRAMER M, Ingwersen M, Teichgraber U, Guttler F, et al
    Added value of chest CT in a machine learning-based prediction model to rule out COVID-19 before inpatient admission: A retrospective university network study.
    Eur J Radiol. 2023;163:110827.
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    September 2022
  11. AZOUR L, Condos R, Keerthivasan MB, Bruno M, et al
    Low-field 0.55 T MRI for assessment of pulmonary groundglass and fibrosis-like opacities: Inter-reader and inter-modality concordance.
    Eur J Radiol. 2022;156:110515.
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    July 2022
  12. SARDANELLI F, Colarieti A
    Imaging of axillary lymph nodes in the COVID-19 era: A lesson to be learned.
    Eur J Radiol. 2022;154:110446.
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  13. CORONADO-GUTIERREZ D, Ganau S, Bargallo X, Ubeda B, et al
    Quantitative ultrasound image analysis of axillary lymph nodes to differentiate malignancy from reactive benign changes due to COVID-19 vaccination.
    Eur J Radiol. 2022;154:110438.
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    May 2022
  14. SEHGAL A, Kumar J, Garg A, Jain A, et al
    MR imaging spectrum in COVID associated Rhino-Orbito-Cerebral mucormycosis with special emphasis on intracranial disease and impact on patient prognosis.
    Eur J Radiol. 2022;152:110341.
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    April 2022
  15. VAN NIJNATTEN TJA, Jochelson MS, Lobbes MBI
    Axillary lymph node characteristics in breast cancer patients versus post-COVID-19 vaccination: Overview of current evidence per imaging modality.
    Eur J Radiol. 2022;152:110334.
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  16. MEZGHANI S, Salga M, Tordjman M, Amar R, et al
    Heterotopic ossification and COVID 19: Imaging analysis of ten consecutive cases.
    Eur J Radiol. 2022;152:110336.
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    March 2022
  17. POLETTI J, Bach M, Yang S, Sexauer R, et al
    Automated lung vessel segmentation reveals blood vessel volume redistribution in viral pneumonia.
    Eur J Radiol. 2022;150:110259.
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  18. PENCE MC, Avdan Aslan A, Tunccan OG, Erbas G, et al
    Prognostic value of semi-quantitative CT-based score integrated with cardiovascular risk factors during the first peak of the COVID-19 pandemic: A new score to predict poor outcome.
    Eur J Radiol. 2022;150:110238.
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    February 2022
  19. ONNIS C, Muscogiuri G, Paolo Bassareo P, Cau R, et al
    Non-invasive coronary imaging in patients with COVID-19: A narrative review.
    Eur J Radiol. 2022;149:110188.
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    January 2022
  20. GIL-RODRIGUEZ J, Perez de Rojas J, Aranda-Laserna P, Benavente-Fernandez A, et al
    Ultrasound findings of lung ultrasonography in COVID-19: A systematic review.
    Eur J Radiol. 2022;148:110156.
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  21. CAU R, Faa G, Nardi V, Balestrieri A, et al
    Long-COVID diagnosis: From diagnostic to advanced AI-driven models.
    Eur J Radiol. 2022;148:110164.
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  22. CHEN JY, Vedantham S, Lexa FJ
    Burnout and work-work imbalance in radiology- wicked problems on a global scale. A baseline pre-COVID-19 survey of US neuroradiologists compared to international radiologists and adjacent staff.
    Eur J Radiol. 2022 Jan 7:110153. doi: 10.1016/j.ejrad.2022.110153.
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    November 2021
  23. WANG L, Wang H, Huang Y, Yan B, et al
    Trends in the application of deep learning networks in medical image analysis: Evolution between 2012 and 2020.
    Eur J Radiol. 2021;146:110069.
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  24. SHANG S, Huang C, Yan W, Chen R, et al
    Performance of a computer aided diagnosis system for SARS-CoV-2 pneumonia based on ultrasound images.
    Eur J Radiol. 2021;146:110066.
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  25. KRIZA C, Amenta V, Zenie A, Panidis D, et al
    Artificial intelligence for imaging-based COVID-19 detection: Systematic review comparing added value of AI versus human readers.
    Eur J Radiol. 2021;145:110028.
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  26. CHANDARANA H, Pisuchpen N, Krieger R, Dane B, et al
    Association of body composition parameters measured on CT with risk of hospitalization in patients with Covid-19.
    Eur J Radiol. 2021;145:110031.
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    October 2021
  27. GIANNAKIS A, More D, Erdmann S, Kintzele L, et al
    COVID-19 pneumonia and its lookalikes: How radiologists perform in differentiating atypical pneumonias.
    Eur J Radiol. 2021;144:110002.
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  28. LI Y, Han X, Huang J, Alwalid O, et al
    Follow-up study of pulmonary sequelae in discharged COVID-19 patients with diabetes or secondary hyperglycemia.
    Eur J Radiol. 2021;144:109997.
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    September 2021
  29. BUSTIN A, Sridi S, Gravinay P, Legghe B, et al
    High-resolution Free-breathing late gadolinium enhancement Cardiovascular magnetic resonance to diagnose myocardial injuries following COVID-19 infection.
    Eur J Radiol. 2021;144:109960.
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    August 2021
  30. TOLONEN A, Pakarinen T, Sassi A, Kytta J, et al
    Methodology, clinical applications, and future directions of body composition analysis using computed tomography (CT) images: A review.
    Eur J Radiol. 2021;145:109943.
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    July 2021
  31. VAN HEUSDEN HC, Swartz JE, Chargi N, de Jong PA, et al
    Feasibility of assessment of skeletal muscle mass on a single cross-sectional image at the level of the fourth thoracic vertebra.
    Eur J Radiol. 2021;142:109879.
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    June 2021
  32. STANZIONE A, Ponsiglione A, Cuocolo R, Brunetti A, et al
    Author response to the Letter to Editor on Chest CT in COVID-19 patients: Structured vs conventional reporting.
    Eur J Radiol. 2021;141:109822.
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  33. AGGARWAL A, Bagri N
    Letter to Editor in response to Chest CT in COVID-19 patients: Structured vs conventional reporting.
    Eur J Radiol. 2021;141:109814.
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    March 2021
  34. BALBI M, Conti C, Imeri G, Caroli A, et al
    Post-discharge chest CT findings and pulmonary function tests in severe COVID-19 patients.
    Eur J Radiol. 2021;138:109676.
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  35. RIZZETTO F, Perillo N, Artioli D, Travaglini F, et al
    Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients.
    Eur J Radiol. 2021;138:109650.
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  36. STANZIONE A, Ponsiglione A, Cuocolo R, Rumolo M, et al
    Chest CT in COVID-19 patients: Structured vs conventional reporting.
    Eur J Radiol. 2021;138:109621.
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    February 2021
  37. ANGELI E, Dalto S, Marchese S, Setti L, et al
    Prognostic value of CT integrated with clinical and laboratory data during the first peak of the COVID-19 pandemic in Northern Italy: A nomogram to predict unfavorable outcome.
    Eur J Radiol. 2021;137:109612.
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  38. VALLE C, Bonaffini PA, Dal Corso M, Mercanzin E, et al
    Association between pulmonary embolism and COVID-19 severe pneumonia: Experience from two centers in the core of the infection Italian peak.
    Eur J Radiol. 2021;137:109613.
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  39. WU Z, Li L, Jin R, Liang L, et al
    Texture feature-based machine learning classifier could assist in the diagnosis of COVID-19.
    Eur J Radiol. 2021;137:109602.
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  40. GONG K, Wu D, Arru CD, Homayounieh F, et al
    A multi-center study of COVID-19 patient prognosis using deep learning-based CT image analysis and electronic health records.
    Eur J Radiol. 2021 Feb 5:109583. doi: 10.1016/j.ejrad.2021.109583.
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    January 2021
  41. WANG L, Kelly B, Lee EH, Wang H, et al
    Multi-classifier-based identification of COVID-19 from chest computed tomography using generalizable and interpretable radiomics features.
    Eur J Radiol. 2021;136:109552.
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    December 2020
  42. BOOZ C, Vogl TJ, Joseph Schoepf U, Caruso D, et al
    Value of minimum intensity projections for chest CT in COVID-19 patients.
    Eur J Radiol. 2020;135:109478.
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  43. LARICI AR, Cicchetti G, Marano R, Merlino B, et al
    Corrigendum to "Multimodality imaging of COVID-19 pneumonia: From diagnosis to follow-up. A comprehensive review" [Eur. J. Radiol. 131 (October) (2020) 109217].
    Eur J Radiol. 2020 Dec 4:109364. doi: 10.1016/j.ejrad.2020.109364.
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    November 2020
  44. LI Q, Huang XT, Li CH, Liu D, et al
    CT features of coronavirus disease 2019 (COVID-19) with an emphasis on the vascular enlargement pattern.
    Eur J Radiol. 2020;134:109442.
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  45. AKYURT N
    Knowledge, practice and emotional status related to COVID-19 pandemic among radiology technicians working at pandemic hospitals.
    Eur J Radiol. 2020;134:109431.
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  46. OHANA M, Muller J, Severac F, Bilbault P, et al
    Temporal variations in the diagnostic performance of chest CT for Covid-19 depending on disease prevalence: Experience from North-Eastern France.
    Eur J Radiol. 2020;134:109425.
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  47. ZHAO P, Pan Z, Yu T
    Corrigendum to "COV is a readily available quantitative indicator of metabolic heterogeneity for predicting survival of patients with early and locally advanced NSCLC manifesting as central lung cancer" [Eur. J. Radiol. 132 (2020) 109338].
    Eur J Radiol. 2020 Nov 13:109401. doi: 10.1016/j.ejrad.2020.109401.
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  48. YATES A, Dempsey PJ, Vencken S, MacMahon PJ, et al
    Structured reporting in portable chest radiographs: An essential tool in the diagnosis of COVID-19.
    Eur J Radiol. 2020;134:109414.
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  49. JAVOR D, Kaplan H, Kaplan A, Puchner SB, et al
    Deep learning analysis provides accurate COVID-19 diagnosis on chest computed tomography.
    Eur J Radiol. 2020;133:109402.
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  50. CHOI Y, Lee MK
    Neuroimaging findings of brain MRI and CT in patients with COVID-19: A systematic review and meta-analysis.
    Eur J Radiol. 2020;133:109393.
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    October 2020
  51. COLOMBI D, Petrini M, Maffi G, Villani GD, et al
    Comparison of admission chest computed tomography and lung ultrasound performance for diagnosis of COVID-19 pneumonia in populations with different disease prevalence.
    Eur J Radiol. 2020;133:109344.
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  52. YU T
    COV is a readily available quantitative indicator of metabolic heterogeneity for predicting survival of patients with early and locally advanced NSCLC manifesting as central lung cancer.
    Eur J Radiol. 2020;132:109338.
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  53. OOI MWX, Rajai A, Patel R, Gerova N, et al
    Pulmonary thromboembolic disease in COVID-19 patients on CT pulmonary angiography - Prevalence, pattern of disease and relationship to D-dimer.
    Eur J Radiol. 2020;132:109336.
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    September 2020
  54. TABATABAEI SMH, Rahimi H, Moghaddas F, Rajebi H, et al
    Predictive value of CT in the short-term mortality of Coronavirus Disease 2019 (COVID-19) pneumonia in nonelderly patients: A case-control study.
    Eur J Radiol. 2020;132:109298.
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  55. FLORIN M, Pinar U, Chavigny E, Bouaboula M, et al
    Socio-economic and psychological impact of the COVID-19 outbreak on private practice and public hospital radiologists.
    Eur J Radiol. 2020;132:109285.
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  56. COZZI A, Schiaffino S, Arpaia F, Della Pepa G, et al
    Chest x-ray in the COVID-19 pandemic: Radiologists' real-world reader performance.
    Eur J Radiol. 2020;132:109272.
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  57. UFUK F, Demirci M, Sagtas E, Akbudak IH, et al
    The prognostic value of pneumonia severity score and pectoralis muscle Area on chest CT in adult COVID-19 patients.
    Eur J Radiol. 2020;131:109271.
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  58. KOTTLORS J, Zopfs D, Fervers P, Bremm J, et al
    Body composition on low dose chest CT is a significant predictor of poor clinical outcome in COVID-19 disease - A multicenter feasibility study.
    Eur J Radiol. 2020;132:109274.
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    August 2020
  59. ANASTASOPOULOS C, Weikert T, Yang S, Abdulkadir A, et al
    Development and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning.
    Eur J Radiol. 2020;131:109233.
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  60. MEILER S, Schaible J, Poschenrieder F, Scharf G, et al
    Can CT performed in the early disease phase predict outcome of patients with COVID 19 pneumonia? Analysis of a cohort of 64 patients from Germany.
    Eur J Radiol. 2020;131:109256.
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  61. OTERINO SERRANO C, Alonso E, Andres M, Buitrago NM, et al
    Pediatric chest x-ray in covid-19 infection.
    Eur J Radiol. 2020;131:109236.
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  62. HUANG Q, Li J, Lyu S, Liang W, et al
    COVID-19 associated kidney impairment in adult: Qualitative and quantitative analyses with non-enhanced CT on admission.
    Eur J Radiol. 2020;131:109240.
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  63. LARICI AR, Cicchetti G, Marano R, Merlino B, et al
    Multimodality imaging of COVID-19 pneumonia: from diagnosis to follow-up. Acomprehensive review.
    Eur J Radiol. 2020;131:109217.
    >> Share

  64. GUILLO E, Bedmar Gomez I, Dangeard S, Bennani S, et al
    COVID-19 pneumonia: Diagnostic and prognostic role of CT based on a retrospective analysis of 214 consecutive patients from Paris, France.
    Eur J Radiol. 2020;131:109209.
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    July 2020
  65. LEONARDI A, Scipione R, Alfieri G, Petrillo R, et al
    Role of computed tomography in predicting critical disease in patients with covid-19 pneumonia: A retrospective study using a semiautomatic quantitative method.
    Eur J Radiol. 2020;130:109202.
    >> Share

  66. FALASCHI Z, Danna PSC, Arioli R, Pasche A, et al
    Chest CT accuracy in diagnosing COVID-19 during the peak of the Italian epidemic: A retrospective correlation with RT-PCR testing and analysis of discordant cases.
    Eur J Radiol. 2020;130:109192.
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    June 2020
  67. PARRY AH, Wani AH, Yaseen M, Dar KA, et al
    Spectrum of chest computed tomographic (CT) findings in coronavirus disease-19 (COVID-19) patients in India.
    Eur J Radiol. 2020;129:109147.
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  68. PATELLI G, Paganoni S, Besana F, Codazzi F, et al
    Preliminary detection of lung hypoperfusion in discharged Covid-19 patients during recovery.
    Eur J Radiol. 2020;129:109121.
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  69. CHAE KJ, Jin GY, Lee CS, Lee HB, et al
    Positive conversion of COVID-19 after two consecutive negative RT-PCR results: A role of low-dose CT.
    Eur J Radiol. 2020;129:109122.
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  70. BORRERO R, Marquez S, Triana G
    Chest CT in coronavirus pandemic. Are there really age based radiological and clinical differences?
    Eur J Radiol. 2020;129:109107.
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    May 2020
  71. IPPOLITO D, Pecorelli A, Maino C, Capodaglio C, et al
    Diagnostic impact of bedside chest X-ray features of 2019 novel coronavirus in the routine admission at the emergency department: case series from Lombardy region.
    Eur J Radiol. 2020;129:109092.
    >> Share

  72. DE BARRY O, Obadia I, Hajjam ME, Carlier RY, et al
    Chest-X-ray is a mainstay for follow-up in critically ill patients with covid-19 induced pneumonia.
    Eur J Radiol. 2020 May 13:109075. doi: 10.1016/j.ejrad.2020.109075.
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  73. SASI S D, Ramaniharan AK, Bhattacharjee R, Gupta RK, et al
    Evaluating feasibility of high resolution T1-perfusion MRI with whole brain coverage using compressed SENSE: Application to glioma grading.
    Eur J Radiol. 2020;129:109049.
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  74. WU X, Hui H, Niu M, Li L, et al
    Deep learning-based multi-view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study.
    Eur J Radiol. 2020;128:109041.
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    April 2020
  75. ZHAO Y, Xiang C, Wang S, Peng C, et al
    Radiology department strategies to protect radiologic technologists against COVID19: Experience from Wuhan.
    Eur J Radiol. 2020;127:108996.
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  76. HU Q, Guan H, Sun Z, Huang L, et al
    Early CT features and temporal lung changes in COVID-19 pneumonia in Wuhan, China.
    Eur J Radiol. 2020;128:109017.
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  77. YANG Q, Liu Q, Xu H, Lu H, et al
    Imaging of coronavirus disease 2019: A Chinese expert consensus statement.
    Eur J Radiol. 2020;127:109008.
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  78. DOU P, Zhang S, Wang C, Cai L, et al
    Serial CT features in discharged COVID-19 patients with positive RT-PCR re-test.
    Eur J Radiol. 2020;127:109010.
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  79. DING X, Xu J, Zhou J, Long Q, et al
    Chest CT findings of COVID-19 pneumonia by duration of symptoms.
    Eur J Radiol. 2020;127:109009.
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    March 2020
  80. LONG C, Xu H, Shen Q, Zhang X, et al
    Diagnosis of the Coronavirus disease (COVID-19): rRT-PCR or CT?
    Eur J Radiol. 2020;126:108961.
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  81. CHEN Z, Fan H, Cai J, Li Y, et al
    High-resolution computed tomography manifestations of COVID-19 infections in patients of different ages.
    Eur J Radiol. 2020;126:108972.
    >> Share

  82. LING Z, Xu X, Gan Q, Zhang L, et al
    Asymptomatic SARS-CoV-2 infected patients with persistent negative CT findings.
    Eur J Radiol. 2020;126:108956.
    >> Share

  83. LIU KC, Xu P, Lv WF, Qiu XH, et al
    CT manifestations of coronavirus disease-2019: A retrospective analysis of 73 cases by disease severity.
    Eur J Radiol. 2020;126:108941.
    >> Share


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