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1.
Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs.
Radiology
; 294(1): 199-209, 2020 01.
Article
in English
| MEDLINE | ID: mdl-31714194
2.
Beyond the AJR: An International Competition Advances Artificial Intelligence Research.
AJR Am J Roentgenol
; 222(1): e2329644, 2024 01.
Article
in English
| MEDLINE | ID: mdl-37222276
3.
Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability.
Skeletal Radiol
; 48(2): 275-283, 2019 Feb.
Article
in English
| MEDLINE | ID: mdl-30069585
4.
Beyond Human Perception: Sexual Dimorphism in Hand and Wrist Radiographs Is Discernible by a Deep Learning Model.
J Digit Imaging
; 32(4): 665-671, 2019 08.
Article
in English
| MEDLINE | ID: mdl-30478479
5.
Artificial Intelligence Applied to Contrast-enhanced Mammography: Exploring Uncharted Territory.
Radiology
; 307(5): e231140, 2023 06.
Article
in English
| MEDLINE | ID: mdl-37338358
6.
Current Applications and Future Impact of Machine Learning in Radiology.
Radiology
; 288(2): 318-328, 2018 Aug.
Article
in English
| MEDLINE | ID: mdl-29944078
7.
Quantifying the effect of slice thickness, intravenous contrast and tube current on muscle segmentation: Implications for body composition analysis.
Eur Radiol
; 28(6): 2455-2463, 2018 Jun.
Article
in English
| MEDLINE | ID: mdl-29318425
8.
A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection.
J Digit Imaging
; 31(4): 393-402, 2018 08.
Article
in English
| MEDLINE | ID: mdl-28983851
9.
Iterative Image Reconstruction Improves the Accuracy of Automated Plaque Burden Assessment in Coronary CT Angiography: A Comparison With Intravascular Ultrasound.
AJR Am J Roentgenol
; 208(4): 777-784, 2017 Apr.
Article
in English
| MEDLINE | ID: mdl-28177655
10.
Fully Automated Deep Learning System for Bone Age Assessment.
J Digit Imaging
; 30(4): 427-441, 2017 Aug.
Article
in English
| MEDLINE | ID: mdl-28275919
11.
Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis.
J Digit Imaging
; 30(4): 487-498, 2017 Aug.
Article
in English
| MEDLINE | ID: mdl-28653123
12.
Ultralow-Dose Abdominal Computed Tomography: Comparison of 2 Iterative Reconstruction Techniques in a Prospective Clinical Study.
J Comput Assist Tomogr
; 39(4): 489-98, 2015.
Article
in English
| MEDLINE | ID: mdl-26182223
13.
Assessment of Filtered Back Projection, Adaptive Statistical, and Model-Based Iterative Reconstruction for Reduced Dose Abdominal Computed Tomography.
J Comput Assist Tomogr
; 39(4): 462-7, 2015.
Article
in English
| MEDLINE | ID: mdl-25734468
14.
Dose reduction for chest CT: comparison of two iterative reconstruction techniques.
Acta Radiol
; 56(6): 688-95, 2015 Jun.
Article
in English
| MEDLINE | ID: mdl-24948790
15.
Crystal analyser-based X-ray phase contrast imaging in the dark field: implementation and evaluation using excised tissue specimens.
Eur Radiol
; 24(2): 423-33, 2014 Feb.
Article
in English
| MEDLINE | ID: mdl-24048725
16.
Submillisievert chest CT with filtered back projection and iterative reconstruction techniques.
AJR Am J Roentgenol
; 203(4): 772-81, 2014 Oct.
Article
in English
| MEDLINE | ID: mdl-25247943
17.
Role of compressive sensing technique in dose reduction for chest computed tomography: a prospective blinded clinical study.
J Comput Assist Tomogr
; 38(5): 760-7, 2014.
Article
in English
| MEDLINE | ID: mdl-24834892
18.
Computed tomography (CT) of the chest at less than 1 mSv: an ongoing prospective clinical trial of chest CT at submillisievert radiation doses with iterative model image reconstruction and iDose4 technique.
J Comput Assist Tomogr
; 38(4): 613-9, 2014.
Article
in English
| MEDLINE | ID: mdl-24651746
19.
Preliminary results: prospective clinical study to assess image-based iterative reconstruction for abdominal computed tomography acquired at 2 radiation dose levels.
J Comput Assist Tomogr
; 38(1): 117-22, 2014.
Article
in English
| MEDLINE | ID: mdl-24424560
20.
Deep-Learning Based Automated Segmentation and Quantitative Volumetric Analysis of Orbital Muscle and Fat for Diagnosis of Thyroid Eye Disease.
Invest Ophthalmol Vis Sci
; 65(5): 6, 2024 May 01.
Article
in English
| MEDLINE | ID: mdl-38696188