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1
Chest CT score in COVID-19 patients: correlation with disease severity and short-term prognosis
Chest CT score in COVID-19 patients: correlation with disease severity and short-term prognosis
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Chest CT score in COVID-19 patients: correlation with disease severity and short-term prognosis

European radiology, 2020-12, Vol.30 (12), p.6808-6817 [Peer Reviewed Journal]

European Society of Radiology 2020 ;European Society of Radiology 2020. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-020-07033-y ;PMID: 32623505

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2
CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)
CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)
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CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)

European radiology, 2020-08, Vol.30 (8), p.4407-4416 [Peer Reviewed Journal]

European Society of Radiology 2020 ;European Society of Radiology 2020. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-020-06817-6 ;PMID: 32215691

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3
Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network
Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network
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Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network

European radiology, 2019-11, Vol.29 (11), p.6191-6201 [Peer Reviewed Journal]

The Author(s) 2019 ;European Radiology is a copyright of Springer, (2019). All Rights Reserved. © 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-019-06163-2 ;PMID: 31041565

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4
Coronavirus disease 2019: initial chest CT findings
Coronavirus disease 2019: initial chest CT findings
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Coronavirus disease 2019: initial chest CT findings

European radiology, 2020-08, Vol.30 (8), p.4398-4406 [Peer Reviewed Journal]

European Society of Radiology 2020 ;European Society of Radiology 2020. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-020-06816-7 ;PMID: 32211963

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5
Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores
Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores
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Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores

European radiology, 2015-10, Vol.25 (10), p.2840-2850 [Peer Reviewed Journal]

European Society of Radiology 2015 ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-015-3701-8 ;PMID: 25991476

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6
Updated prostate imaging reporting and data system (PIRADS v2) recommendations for the detection of clinically significant prostate cancer using multiparametric MRI: critical evaluation using whole-mount pathology as standard of reference
Updated prostate imaging reporting and data system (PIRADS v2) recommendations for the detection of clinically significant prostate cancer using multiparametric MRI: critical evaluation using whole-mount pathology as standard of reference
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Updated prostate imaging reporting and data system (PIRADS v2) recommendations for the detection of clinically significant prostate cancer using multiparametric MRI: critical evaluation using whole-mount pathology as standard of reference

European radiology, 2016-06, Vol.26 (6), p.1606-1612 [Peer Reviewed Journal]

European Society of Radiology 2015 ;European Society of Radiology 2016 ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-015-4015-6 ;PMID: 26396111

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7
Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT
Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT
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Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT

European radiology, 2019-11, Vol.29 (11), p.6163-6171 [Peer Reviewed Journal]

European Society of Radiology 2019. corrected publication 2019 ;European Radiology is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-019-06170-3 ;PMID: 30976831

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8
Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging
Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging
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Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging

European radiology, 2020-01, Vol.30 (1), p.413-424 [Peer Reviewed Journal]

The Author(s) 2019 ;European Radiology is a copyright of Springer, (2019). All Rights Reserved. © 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-019-06318-1 ;PMID: 31332558

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9
Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT
Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT
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Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT

European radiology, 2019-07, Vol.29 (7), p.3595-3605 [Peer Reviewed Journal]

European Society of Radiology 2019 ;European Radiology is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-018-5985-y ;PMID: 30770969

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10
Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer
Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer
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Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer

European radiology, 2019-03, Vol.29 (3), p.1211-1220 [Peer Reviewed Journal]

European Society of Radiology 2018 ;European Radiology is a copyright of Springer, (2018). All Rights Reserved. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-018-5683-9 ;PMID: 30128616

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11
CT features of SARS-CoV-2 pneumonia according to clinical presentation: a retrospective analysis of 120 consecutive patients from Wuhan city
CT features of SARS-CoV-2 pneumonia according to clinical presentation: a retrospective analysis of 120 consecutive patients from Wuhan city
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CT features of SARS-CoV-2 pneumonia according to clinical presentation: a retrospective analysis of 120 consecutive patients from Wuhan city

European radiology, 2020-08, Vol.30 (8), p.4417-4426 [Peer Reviewed Journal]

European Society of Radiology 2020 ;European Society of Radiology 2020. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-020-06854-1 ;PMID: 32279115

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12
Association of “initial CT” findings with mortality in older patients with coronavirus disease 2019 (COVID-19)
Association of “initial CT” findings with mortality in older patients with coronavirus disease 2019 (COVID-19)
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Association of “initial CT” findings with mortality in older patients with coronavirus disease 2019 (COVID-19)

European radiology, 2020-11, Vol.30 (11), p.6186-6193 [Peer Reviewed Journal]

European Society of Radiology 2020 ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-020-06969-5 ;PMID: 32524220

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13
Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging
Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging
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Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging

European radiology, 2019-08, Vol.29 (8), p.4068-4076 [Peer Reviewed Journal]

European Society of Radiology 2018 ;European Radiology is a copyright of Springer, (2018). All Rights Reserved. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-018-5830-3 ;PMID: 30443758

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14
Patients undergoing recurrent CT scans: assessing the magnitude
Patients undergoing recurrent CT scans: assessing the magnitude
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Patients undergoing recurrent CT scans: assessing the magnitude

European radiology, 2020-04, Vol.30 (4), p.1828-1836 [Peer Reviewed Journal]

European Society of Radiology 2019 ;European Radiology is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-019-06523-y ;PMID: 31792585

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15
Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma
Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma
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Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma

European radiology, 2018-04, Vol.28 (4), p.1625-1633 [Peer Reviewed Journal]

European Society of Radiology 2017 ;European Radiology is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-017-5118-z ;PMID: 29134348

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16
Dual-energy CT–based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer
Dual-energy CT–based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer
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Dual-energy CT–based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer

European radiology, 2020-04, Vol.30 (4), p.2324-2333 [Peer Reviewed Journal]

European Society of Radiology 2020 ;European Radiology is a copyright of Springer, (2020). All Rights Reserved. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-019-06621-x ;PMID: 31953668

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17
Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation
Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation
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Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation

European radiology, 2020-12, Vol.30 (12), p.6770-6778 [Peer Reviewed Journal]

European Society of Radiology 2020 ;European Society of Radiology 2020. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-020-07013-2 ;PMID: 32591888

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18
From community-acquired pneumonia to COVID-19: a deep learning–based method for quantitative analysis of COVID-19 on thick-section CT scans
From community-acquired pneumonia to COVID-19: a deep learning–based method for quantitative analysis of COVID-19 on thick-section CT scans
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From community-acquired pneumonia to COVID-19: a deep learning–based method for quantitative analysis of COVID-19 on thick-section CT scans

European radiology, 2020-12, Vol.30 (12), p.6828-6837 [Peer Reviewed Journal]

European Society of Radiology 2020 ;European Society of Radiology 2020. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-020-07042-x ;PMID: 32683550

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19
Can peritumoral radiomics increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT?
Can peritumoral radiomics increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT?
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Can peritumoral radiomics increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT?

European radiology, 2019-11, Vol.29 (11), p.6049-6058 [Peer Reviewed Journal]

European Society of Radiology 2019 ;European Radiology is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-019-06084-0 ;PMID: 30887209

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20
Can CT-based radiomics signature predict KRAS/NRAS/BRAF mutations in colorectal cancer?
Can CT-based radiomics signature predict KRAS/NRAS/BRAF mutations in colorectal cancer?
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Can CT-based radiomics signature predict KRAS/NRAS/BRAF mutations in colorectal cancer?

European radiology, 2018-05, Vol.28 (5), p.2058-2067 [Peer Reviewed Journal]

European Society of Radiology 2018 ;European Radiology is a copyright of Springer, (2018). All Rights Reserved. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-017-5146-8 ;PMID: 29335867

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