Publications by authors named "Ronald M Summers"

100Publications

Adult patient-specific CT organ dose estimations using automated segmentations and Monte Carlo simulations.

Biomed Phys Eng Express 2020 Jun 12;6(4):045016. Epub 2020 Jun 12.

Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20850, United States of America.

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June 2020

Artificial Intelligence of COVID-19 Imaging: A Hammer in Search of a Nail.

Authors:
Ronald M Summers

Radiology 2020 Dec 22:204226. Epub 2020 Dec 22.

From the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, 10 Center Dr, Bldg 10, Room 1C224D, MSC 1182, Bethesda, MD 20892-1182.

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December 2020

Discriminative ensemble learning for few-shot chest x-ray diagnosis.

Med Image Anal 2020 Nov 19;68:101911. Epub 2020 Nov 19.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892, USA.

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November 2020

Nomograms for Automated Body Composition Analysis: A Crucial Step for Routine Clinical Implementation.

Authors:
Ronald M Summers

Radiology 2020 Nov 24:203956. Epub 2020 Nov 24.

From the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, 10 Center Dr, Bldg 10, Room 1C224D, MSC 1182, Bethesda, MD 20892-1182.

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November 2020

A disentangled generative model for disease decomposition in chest X-rays via normal image synthesis.

Med Image Anal 2021 01 7;67:101839. Epub 2020 Oct 7.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD 20892-1182, USA.

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January 2021

Fully automated CT imaging biomarkers of bone, muscle, and fat: correcting for the effect of intravenous contrast.

Abdom Radiol (NY) 2020 Sep 18. Epub 2020 Sep 18.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA.

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September 2020

Liver Steatosis Categorization on Contrast-Enhanced CT Using a Fully-Automated Deep Learning Volumetric Segmentation Tool: Evaluation in 1,204 Heathy Adults Using Unenhanced CT as Reference Standard.

AJR Am J Roentgenol 2020 Sep 16. Epub 2020 Sep 16.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD.

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September 2020

Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study.

Lancet Digit Health 2020 04 2;2(4):e192-e200. Epub 2020 Mar 2.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD.

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April 2020

Automated Abdominal CT Imaging Biomarkers for Opportunistic Prediction of Future Major Osteoporotic Fractures in Asymptomatic Adults.

Radiology 2020 10 11;297(1):64-72. Epub 2020 Aug 11.

From the Department of Radiology, University of Wisconsin School of Medicine & Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252 (P.J.P., P.M.G., R.Z., S.J.L.); and Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (J.L., V.S., R.M.S.).

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October 2020

Utilizing Fully Automated Abdominal CT-Based Biomarkers for Opportunistic Screening for Metabolic Syndrome in Adults Without Symptoms.

AJR Am J Roentgenol 2021 Jan 10;216(1):85-92. Epub 2020 Nov 10.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD.

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January 2021

On the Interpretability of Artificial Intelligence in Radiology: Challenges and Opportunities.

Radiol Artif Intell 2020 May 27;2(3):e190043. Epub 2020 May 27.

Artorg Center for Biomedical Research, University of Bern, Murtenstrasse 50, 3008 Bern, Switzerland (M.R.); Insel Data Science Center, University of Bern, Bern, Switerland (F.M.D.); Institute of Diagnostic and Interventional Neuroradiology (R.M., R.W.) and Department of Diagnostic, Interventional and Paediatric Radiology (H.v.T.K.), Inselspital University Hospital Bern, Bern, Switzerland; Center for Microelectromechanical Systems-University of Minho Research Unit, University of Minho, Guimarães, Portugal (S.P., C.A.S.); and Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.).

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May 2020

Automated abnormality classification of chest radiographs using deep convolutional neural networks.

NPJ Digit Med 2020 14;3:70. Epub 2020 May 14.

1Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD 20892 USA.

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May 2020

Preparing Medical Imaging Data for Machine Learning.

Radiology 2020 04 18;295(1):4-15. Epub 2020 Feb 18.

From the Department of Radiology, Stanford University School of Medicine, 300 Pasteur Dr, S-072, Stanford, CA 94305-5105 (M.J.W., D.F., D.L.R., M.P.L.); Segmed, Menlo Park, Calif (M.J.W., W.A.K., C.H., J.W.); School of Engineering, Stanford University, Stanford, Calif (J.W.); Institute of Cognitive Neuroscience, University College London, London, England (H.H.); Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (L.R.F.); Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institutes of Health, Clinical Center, Bethesda, Md (R.M.S.); Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, Calif (D.L.R.); and Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI), Stanford, Calif (M.P.L.).

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April 2020

The Evolving Status of Radiomics.

J Natl Cancer Inst 2020 Sep;112(9):869-870

Imaging Biomarkers and Computer-Aided, Diagnosis Laboratory NIH Clinical Center, Bethesda, MD, USA.

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September 2020

Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks.

Sci Rep 2019 11 15;9(1):16884. Epub 2019 Nov 15.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Building 10 Room 1C224D MSC 1182, Bethesda, MD, 20892-1182, USA.

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November 2019

Erratum: Prostate cancer detection from multi-institution multiparametric MRIs using deep convolutional neural networks system (Erratum).

J Med Imaging (Bellingham) 2019 Jul 27;6(3):039803. Epub 2019 Sep 27.

National Institutes of Health Clinical Center, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Bethesda, Maryland, United States.

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July 2019

Technical and Clinical Factors Affecting Success Rate of a Deep Learning Method for Pancreas Segmentation on CT.

Acad Radiol 2020 05 16;27(5):689-695. Epub 2019 Sep 16.

Imaging Biomarkers and Computer-aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, Clinical Center, National Institutes of Health, Building 10 Room 1C224D MSC 1182, Bethesda, MD 20892-1182. Electronic address:

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May 2020

Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment.

Radiology 2019 11 17;293(2):334-342. Epub 2019 Sep 17.

From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, Wis 53792-3252 (P.M.G., P.J.P.); and Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (V.S., R.M.S.).

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November 2019

Artificial Intelligence in Musculoskeletal Imaging: A Paradigm Shift.

J Bone Miner Res 2020 01 9;35(1):28-35. Epub 2019 Aug 9.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, Clinical Center, National Institutes of Health, Bethesda, MD, USA.

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January 2020

Fully automated prostate whole gland and central gland segmentation on MRI using holistically nested networks with short connections.

J Med Imaging (Bellingham) 2019 Apr 5;6(2):024007. Epub 2019 Jun 5.

National Institutes of Health Clinical Center, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Bethesda, Maryland, United States.

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April 2019

Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment.

Br J Radiol 2019 Aug 24;92(1100):20190327. Epub 2019 Jun 24.

2 Radiology and Imaging Sciences, National Institutes of Health Clinical Center, 10 Center Drive, Bethesda, MD 20892-1182.

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August 2019

A Road Map for Translational Research on Artificial Intelligence in Medical Imaging: From the 2018 National Institutes of Health/RSNA/ACR/The Academy Workshop.

J Am Coll Radiol 2019 Sep 28;16(9 Pt A):1179-1189. Epub 2019 May 28.

Research Sciences & Strategic Directions, Office of the Director, National Institute of Biomedical Imaging and Bioengineering, The National Institutes of Health, Bethesda, Maryland.

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September 2019

A Machine Learning Algorithm to Estimate Sarcopenia on Abdominal CT.

Acad Radiol 2020 03 22;27(3):311-320. Epub 2019 May 22.

Imaging Biomarkers and Computer-Aided Detection Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Building 10, 1C224, MSC1182, Bethesda, MD 20892-1182. Electronic address:

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March 2020

Automated segmentation and quantification of aortic calcification at abdominal CT: application of a deep learning-based algorithm to a longitudinal screening cohort.

Abdom Radiol (NY) 2019 08;44(8):2921-2928

E3/311 Clinical Science Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave., Madison, WI, 53792-3252, USA.

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August 2019

Opportunistic Osteoporosis Screening at Routine Abdominal and Thoracic CT: Normative L1 Trabecular Attenuation Values in More than 20 000 Adults.

Radiology 2019 05 26;291(2):360-367. Epub 2019 Mar 26.

From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252 (S.J., P.M.G., T.J.Z., S.J.L., P.J.P.); and Department of Diagnostic Radiology, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.).

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May 2019

Prostate cancer detection from multi-institution multiparametric MRIs using deep convolutional neural networks.

J Med Imaging (Bellingham) 2018 Oct 15;5(4):044507. Epub 2018 Dec 15.

National Institutes of Health Clinical Center, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Bethesda, Maryland, United States.

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October 2018

Population-based opportunistic osteoporosis screening: Validation of a fully automated CT tool for assessing longitudinal BMD changes.

Br J Radiol 2019 Feb 28;92(1094):20180726. Epub 2018 Nov 28.

2 Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center , Bethesda, MD , USA.

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February 2019

Deep learning in medical imaging and radiation therapy.

Med Phys 2019 Jan 20;46(1):e1-e36. Epub 2018 Nov 20.

Department of Radiology, University of Chicago, Chicago, IL, 60637, USA.

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January 2019

DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning.

J Med Imaging (Bellingham) 2018 Jul 20;5(3):036501. Epub 2018 Jul 20.

National Institutes of Health, Clinical Center, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Bethesda, Maryland, United States.

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July 2018

Are we at a crossroads or a plateau? Radiomics and machine learning in abdominal oncology imaging.

Authors:
Ronald M Summers

Abdom Radiol (NY) 2019 06;44(6):1985-1989

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, National Institutes of Health Clinical Center, Bldg. 10 Room 1C224D, MSC 1182, Bethesda, MD, 20892-1182, USA.

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June 2019

Holistic classification of CT attenuation patterns for interstitial lung diseases via deep convolutional neural networks.

Comput Methods Biomech Biomed Eng Imaging Vis 2018 6;6(1):1-6. Epub 2016 Jun 6.

Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, USA.

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June 2016

Deep Learning Lends a Hand to Pediatric Radiology.

Authors:
Ronald M Summers

Radiology 2018 04;287(1):323-325

From the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, Clinical Center, National Institutes of Health, Building 10, Room 1C224D, MSC 1182, Bethesda, MD 20892-1182.

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April 2018

Fully automated segmentation and quantification of visceral and subcutaneous fat at abdominal CT: application to a longitudinal adult screening cohort.

Br J Radiol 2018 Sep 28;91(1089):20170968. Epub 2018 Mar 28.

1 Department of Radiology, University of Wisconsin School of Medicine and Public Health , Madison, WI , USA.

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September 2018

Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.

Med Image Anal 2018 04 1;45:94-107. Epub 2018 Feb 1.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Clinical Image Processing Service, Radiology and Imaging Sciences Department, National Institutes of Health Clinical Center, Bethesda, MD 20892-1182, USA. Electronic address:

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April 2018

Special Section Guest Editorial: Radiomics and Deep Learning.

J Med Imaging (Bellingham) 2017 Oct 4;4(4):041301. Epub 2018 Jan 4.

The University of Chicago, Radiology Department, Chicago, Illinois.

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October 2017

Holistic segmentation of the lung in cine MRI.

J Med Imaging (Bellingham) 2017 Oct 30;4(4):041310. Epub 2017 Nov 30.

National Institutes of Health, Radiology and Imaging Sciences, Clinical Center, Clinical Image Processing Services, Bethesda, Maryland, United States.

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October 2017

Automatic magnetic resonance prostate segmentation by deep learning with holistically nested networks.

J Med Imaging (Bellingham) 2017 Oct 21;4(4):041302. Epub 2017 Aug 21.

Imaging Biomarkers and CAD Laboratory, Clinical Center, NIH, Bethesda, Maryland, United States.

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October 2017

Validation of the Dominant Sequence Paradigm and Role of Dynamic Contrast-enhanced Imaging in PI-RADS Version 2.

Radiology 2017 12 19;285(3):859-869. Epub 2017 Jul 19.

From the Molecular Imaging (M.D.G., F.V.M., P.L.C., B.T.) and Biometric Research (J.H.S.) Programs, Laboratory of Pathology (M.J.M.), and Urologic Oncology Branch (P.A.P.), National Cancer Institute, National Institutes of Health, 10 Center Dr, Room B3B85, Bethesda, MD 20892; Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (N.L., R.M.S.); Department of Radiology, University of Cambridge School of Medicine, Cambridge, England (T.B.); Department of Radiology, Universidade Federal Fluminense, Rio de Janeiro, Brazil (L.K.B.); Department of Body Imaging, CDPI Clinics/DASA, Rio de Janeiro, Brazil (L.K.B.); Department of Radiology, George Washington University Hospital, Washington, DC (S.B.); Department of Radiology, Hacettepe University, Ankara, Turkey (I.M.K.); Department of Diagnostic Radiology Singapore General Hospital, Singapore (Y.M.L.); Department of Radiology, Walter Reed National Military Medical Center, Bethesda, Md (J.M.); Department of Radiology, Nephrology Center, Mansoura University, Mansoura, Egypt (H.S.); Center for Interventional Oncology, National Cancer Institute and Clinical Center, and Radiology Imaging Sciences, National Institutes of Health, Bethesda, Md (B.J.W.).

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December 2017

Detection of prostate cancer in multiparametric MRI using random forest with instance weighting.

J Med Imaging (Bellingham) 2017 Apr 12;4(2):024506. Epub 2017 Jun 12.

National Institutes of Health, Clinical Center, Imaging Biomarkers and Computer Aided Diagnosis Laboratory, Bethesda, Maryland, United States.

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April 2017

Mixed spine metastasis detection through positron emission tomography/computed tomography synthesis and multiclassifier.

J Med Imaging (Bellingham) 2017 Apr 5;4(2):024504. Epub 2017 Jun 5.

National Institutes of Health, Radiology and Imaging Sciences Department, Clinical Center, Bethesda, Maryland, United States.

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April 2017

Detection and diagnosis of colitis on computed tomography using deep convolutional neural networks.

Med Phys 2017 Sep 18;44(9):4630-4642. Epub 2017 Jul 18.

Imaging Biomarkers and Computer-aided Diagnosis Laboratory and Clinical Image Processing Service, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.

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September 2017

Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset Session.

J Digit Imaging 2017 Aug;30(4):392-399

University of Colorado School of Medicine, 3401 Shore Rd, Fort Collins, CO, 80524, USA.

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August 2017

Vertebral Body Compression Fractures and Bone Density: Automated Detection and Classification on CT Images.

Radiology 2017 09 16;284(3):788-797. Epub 2017 Mar 16.

From the Department of Radiological Sciences, University of California-Irvine School of Medicine, Orange, Calif (J.E.B.); and Imaging Biomarkers and Computer-Aided Detection Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Building 10, Room 1C224, MSC1182, Bethesda, MD 20892-1182 (J.Y., R.M.S.).

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September 2017

Comparative Evaluation of Three Software Packages for Liver and Spleen Segmentation and Volumetry.

Acad Radiol 2017 07 28;24(7):831-839. Epub 2017 Feb 28.

Clinical Image Processing Service, National Institutes of Health Clinical Center, Bethesda, Maryland; Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, 10 Center Dr., Building 10, Rm. 1C224D MSC 1182, Bethesda, MD 20892-1182. Electronic address:

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July 2017

Texture analysis in radiology: Does the emperor have no clothes?

Authors:
Ronald M Summers

Abdom Radiol (NY) 2017 02;42(2):342-345

Imaging Biomarkers and Computer-aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bldg. 10, Room 1C224D MSC 1182, Bethesda, MD, 20892-1182, USA.

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February 2017

Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest.

Med Phys 2016 Jul;43(7):4362

Imaging Biomarkers and Computer-aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center Building, 10 Room 1C224 MSC 1182, Bethesda, Maryland 20892-1182.

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July 2016

Progress in Fully Automated Abdominal CT Interpretation.

Authors:
Ronald M Summers

AJR Am J Roentgenol 2016 Jul 21;207(1):67-79. Epub 2016 Apr 21.

1 Imaging Biomarkers and Computer-aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bldg 10, Rm 1C224D, MSC 1182, Bethesda, MD 20892-1182.

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July 2016

Regional infarction identification from cardiac CT images: a computer-aided biomechanical approach.

Int J Comput Assist Radiol Surg 2016 Sep 12;11(9):1573-83. Epub 2016 Apr 12.

Radiology and Imaging Sciences, Clinical Center, NIH, Bethesda, MD, USA.

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September 2016

Automated segmentation of the thyroid gland on thoracic CT scans by multiatlas label fusion and random forest classification.

J Med Imaging (Bellingham) 2015 Oct 30;2(4):044006. Epub 2015 Dec 30.

National Institutes of Health Clinical Center , Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Building 10, Room 1C224, MSC 1182, Bethesda, Maryland 20892-1182, United States.

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October 2015

Open-Source Radiation Exposure Extraction Engine (RE3) with Patient-Specific Outlier Detection.

J Digit Imaging 2016 08;29(4):406-19

National Institutes of Health, Clinical Center, Radiology and Imaging Sciences, Clinical Image Processing Service (CIPS), 10 Center Drive, Bethesda, MD, 20892-1182, USA.

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August 2016

Abdominal multi-organ segmentation from CT images using conditional shape-location and unsupervised intensity priors.

Med Image Anal 2015 Dec 4;26(1):1-18. Epub 2015 Jul 4.

Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan. Electronic address:

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December 2015

Automated Detection, Localization, and Classification of Traumatic Vertebral Body Fractures in the Thoracic and Lumbar Spine at CT.

Radiology 2016 Jan 14;278(1):64-73. Epub 2015 Jul 14.

From the Department of Radiological Sciences, University of California-Irvine, Orange, Calif (J.E.B.); and Imaging Biomarkers and Computer-Aided Detection Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, 10 Center Dr, Building 10, 1C224, MSC1182, Bethesda, MD 20892-1182 (J.Y., H.M., R.M.S.).

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January 2016

Automated prostate cancer detection using T2-weighted and high-b-value diffusion-weighted magnetic resonance imaging.

Med Phys 2015 May;42(5):2368-78

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Clinical Center, National Institutes of Health, Bethesda, Maryland 20892.

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May 2015

Automatic multi-resolution shape modeling of multi-organ structures.

Med Image Anal 2015 Oct 15;25(1):11-21. Epub 2015 Apr 15.

Sheikh Zayed Institute for Pediatric Surgical Innovation Children's National Health System, Washington DC 20009, USA; School of Medicine and Health Sciences, George Washington University, Washington DC, USA. Electronic address:

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October 2015

Tumor growth prediction with reaction-diffusion and hyperelastic biomechanical model by physiological data fusion.

Med Image Anal 2015 Oct 17;25(1):72-85. Epub 2015 Apr 17.

Clinical Image Processing Service, Radiology and Imaging Sciences, Clinical Center, NIH, Bethesda, MD, USA. Electronic address:

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October 2015

Computer-aided detection of renal calculi from noncontrast CT images using TV-flow and MSER features.

Med Phys 2015 Jan;42(1):144-53

Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Maryland 20892-1182.

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January 2015

Associations among pericolonic fat, visceral fat, and colorectal polyps on CT colonography.

Obesity (Silver Spring) 2015 Feb 31;23(2):408-14. Epub 2014 Dec 31.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.

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February 2015

Computer aided-diagnosis of prostate cancer on multiparametric MRI: a technical review of current research.

Biomed Res Int 2014 1;2014:789561. Epub 2014 Dec 1.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10, Room 1C224, Bethesda, MD 20892-1182, USA.

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August 2015

Sequential Monte Carlo tracking of the marginal artery by multiple cue fusion and random forest regression.

Med Image Anal 2015 Jan 13;19(1):164-75. Epub 2014 Oct 13.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Building 10 Room 1C224D MSC 1182, Bethesda, MD 20892-1182, United States. Electronic address:

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January 2015

Optimizing area under the ROC curve using semi-supervised learning.

Pattern Recognit 2015 Jan;48(1):276-287

Imaging Biomarkers and Computer-Aided Diagnosis Lab, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD 20892-1182, United States.

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January 2015

Computer-aided detection of exophytic renal lesions on non-contrast CT images.

Med Image Anal 2015 Jan 15;19(1):15-29. Epub 2014 Aug 15.

Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA. Electronic address:

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January 2015

Tumor response assessment using volumetric doubling time: better than RECIST?

Authors:
Ronald M Summers

Acad Radiol 2014 Aug;21(8):947-9

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bldg. 10, Room 1C224D MSC 1182, Bethesda, MD 20892-1182. Electronic address:

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August 2014

Computer aided detection of epidural masses on computed tomography scans.

Comput Med Imaging Graph 2014 Oct 9;38(7):606-12. Epub 2014 May 9.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, Clinical Center, National Institutes of Health, Bethesda, MD, USA. Electronic address:

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October 2014

Tumor sensitive matching flow: A variational method to detecting and segmenting perihepatic and perisplenic ovarian cancer metastases on contrast-enhanced abdominal CT.

Med Image Anal 2014 Jul 18;18(5):725-39. Epub 2014 Apr 18.

Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA. Electronic address:

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July 2014

Cortical shell unwrapping for vertebral body abnormality detection on computed tomography.

Comput Med Imaging Graph 2014 Oct 13;38(7):628-38. Epub 2014 Apr 13.

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, USA.

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October 2014

Patient specific tumor growth prediction using multimodal images.

Med Image Anal 2014 Apr 20;18(3):555-66. Epub 2014 Feb 20.

Clinical Image Processing Service, Radiology and Imaging Sciences, NIH, United States. Electronic address:

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April 2014

Sequential Monte Carlo tracking for marginal artery segmentation on CT angiography by multiple cue fusion.

Med Image Comput Comput Assist Interv 2013 ;16(Pt 2):518-25

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.

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April 2014

A variational framework for joint detection and segmentation of ovarian cancer metastases.

Med Image Comput Comput Assist Interv 2013 ;16(Pt 2):83-90

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Science, National Institutes of Health Clincial Center, Bethesda, MD 20892, USA.

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April 2014

Multimodal image driven patient specific tumor growth modeling.

Med Image Comput Comput Assist Interv 2013 ;16(Pt 3):283-90

Radiology and Imaging Sciences, NIH, USA.

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February 2014

Abdominal multi-organ CT segmentation using organ correlation graph and prediction-based shape and location priors.

Med Image Comput Comput Assist Interv 2013 ;16(Pt 3):275-82

Department of Radiology, Graduate School of Medicine Osaka University, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan.

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February 2014

Manifold diffusion for exophytic kidney lesion detection on non-contrast CT images.

Med Image Comput Comput Assist Interv 2013 ;16(Pt 1):340-7

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Science, National Institutes of Health Clinical Center, Bethesda, MD 20892, USA.

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February 2014

Visual phrase learning and its application in computed tomographic colonography.

Med Image Comput Comput Assist Interv 2013 ;16(Pt 1):243-50

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bldg 10, Room 1C224, Bethesda, MD 20892-1182, USA.

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February 2014

Feasibility of using the marginal blood vessels as reference landmarks for CT colonography.

AJR Am J Roentgenol 2014 Jan;202(1):W50-8

1 Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bldg 10, Rm 1C224D MSC 1182, Bethesda, MD 20892-1182.

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January 2014

A framework to measure myocardial extracellular volume fraction using dual-phase low dose CT images.

Med Phys 2013 Oct;40(10):103501

Clinical Image Processing Service, Radiology and Imaging Sciences, NIH Clinical Center, Bethesda, Maryland 20892.

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October 2013