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10 Steps to Strategically Build and Implement your Enterprise Imaging System: HIMSS-SIIM Collaborative White Paper.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 535, doi. 10.1007/s10278-019-00236-w
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Automated Detection of Measurements and Their Descriptors in Radiology Reports Using a Hybrid Natural Language Processing Algorithm.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 544, doi. 10.1007/s10278-019-00237-9
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Toward Complete Structured Information Extraction from Radiology Reports Using Machine Learning.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 554, doi. 10.1007/s10278-019-00234-y
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Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 565, doi. 10.1007/s10278-019-00244-w
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RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 571, doi. 10.1007/s10278-019-00232-0
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- Article
Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 582, doi. 10.1007/s10278-019-00227-x
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Eye Tracking for Deep Learning Segmentation Using Convolutional Neural Networks.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 597, doi. 10.1007/s10278-019-00220-4
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- Article
Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 605, doi. 10.1007/s10278-019-00182-7
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- Article
Reduction of False-Positive Markings on Mammograms: a Retrospective Comparison Study Using an Artificial Intelligence-Based CAD.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 618, doi. 10.1007/s10278-018-0168-6
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Improved Cancer Detection Using Artificial Intelligence: a Retrospective Evaluation of Missed Cancers on Mammography.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 625, doi. 10.1007/s10278-019-00192-5
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- Article
The Classification of Renal Cancer in 3-Phase CT Images Using a Deep Learning Method.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 638, doi. 10.1007/s10278-019-00230-2
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- Article
Lens Identification to Prevent Radiation-Induced Cataracts Using Convolutional Neural Networks.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 644, doi. 10.1007/s10278-019-00242-y
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Assessment of Critical Feeding Tube Malpositions on Radiographs Using Deep Learning.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 651, doi. 10.1007/s10278-019-00229-9
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- Article
Effectiveness of Deep Learning Algorithms to Determine Laterality in Radiographs.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 656, doi. 10.1007/s10278-019-00226-y
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Beyond Human Perception: Sexual Dimorphism in Hand and Wrist Radiographs Is Discernible by a Deep Learning Model.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 665, doi. 10.1007/s10278-018-0148-x
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Ankle Fracture Detection Utilizing a Convolutional Neural Network Ensemble Implemented with a Small Sample, De Novo Training, and Multiview Incorporation.
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- Journal of Digital Imaging, 2019, v. 32, n. 4, p. 672, doi. 10.1007/s10278-018-0167-7
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