Harvard Catalyst Profiles

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Synho Do, Ph.D.

Concepts

This page shows the publications Synho Do has written about Humans.
Connection Strength

0.120
  1. Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning. Korean J Radiol. 2020 01; 21(1):33-41.
    View in: PubMed
    Score: 0.010
  2. Beyond Human Perception: Sexual Dimorphism in Hand and Wrist Radiographs Is Discernible by a Deep Learning Model. J Digit Imaging. 2019 08; 32(4):665-671.
    View in: PubMed
    Score: 0.010
  3. A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection. J Digit Imaging. 2018 08; 31(4):393-402.
    View in: PubMed
    Score: 0.009
  4. Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability. Skeletal Radiol. 2019 Feb; 48(2):275-283.
    View in: PubMed
    Score: 0.009
  5. Fully Automated Deep Learning System for Bone Age Assessment. J Digit Imaging. 2017 Aug; 30(4):427-441.
    View in: PubMed
    Score: 0.009
  6. Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis. J Digit Imaging. 2017 Aug; 30(4):487-498.
    View in: PubMed
    Score: 0.009
  7. High fidelity system modeling for high quality image reconstruction in clinical CT. PLoS One. 2014; 9(11):e111625.
    View in: PubMed
    Score: 0.007
  8. Automated quantification of pneumothorax in CT. Comput Math Methods Med. 2012; 2012:736320.
    View in: PubMed
    Score: 0.006
  9. A decomposition-based CT reconstruction formulation for reducing blooming artifacts. Phys Med Biol. 2011 Nov 21; 56(22):7109-25.
    View in: PubMed
    Score: 0.006
  10. Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs. Radiology. 2020 01; 294(1):199-209.
    View in: PubMed
    Score: 0.002
  11. Current Applications and Future Impact of Machine Learning in Radiology. Radiology. 2018 Aug; 288(2):318-328.
    View in: PubMed
    Score: 0.002
  12. Interventional Radiology Training Using a Dynamic Medical Immersive Training Environment (DynaMITE). J Am Coll Radiol. 2018 05; 15(5):789-793.
    View in: PubMed
    Score: 0.002
  13. Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success. J Am Coll Radiol. 2018 03; 15(3 Pt B):504-508.
    View in: PubMed
    Score: 0.002
  14. Quantifying the effect of slice thickness, intravenous contrast and tube current on muscle segmentation: Implications for body composition analysis. Eur Radiol. 2018 Jun; 28(6):2455-2463.
    View in: PubMed
    Score: 0.002
  15. Iterative Image Reconstruction Improves the Accuracy of Automated Plaque Burden Assessment in Coronary CT Angiography: A Comparison With Intravascular Ultrasound. AJR Am J Roentgenol. 2017 Apr; 208(4):777-784.
    View in: PubMed
    Score: 0.002
  16. Assessment of Filtered Back Projection, Adaptive Statistical, and Model-Based Iterative Reconstruction for Reduced Dose Abdominal Computed Tomography. J Comput Assist Tomogr. 2015 Jul-Aug; 39(4):462-7.
    View in: PubMed
    Score: 0.002
  17. Ultralow-Dose Abdominal Computed Tomography: Comparison of 2 Iterative Reconstruction Techniques in a Prospective Clinical Study. J Comput Assist Tomogr. 2015 Jul-Aug; 39(4):489-98.
    View in: PubMed
    Score: 0.002
  18. Ultra-low dose abdominal MDCT: using a knowledge-based Iterative Model Reconstruction technique for substantial dose reduction in a prospective clinical study. Eur J Radiol. 2015 Jan; 84(1):2-10.
    View in: PubMed
    Score: 0.002
  19. Submillisievert chest CT with filtered back projection and iterative reconstruction techniques. AJR Am J Roentgenol. 2014 Oct; 203(4):772-81.
    View in: PubMed
    Score: 0.002
  20. Role of compressive sensing technique in dose reduction for chest computed tomography: a prospective blinded clinical study. J Comput Assist Tomogr. 2014 Sep-Oct; 38(5):760-7.
    View in: PubMed
    Score: 0.002
  21. 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. 2014 Jul-Aug; 38(4):613-9.
    View in: PubMed
    Score: 0.002
  22. Dose reduction for chest CT: comparison of two iterative reconstruction techniques. Acta Radiol. 2015 Jun; 56(6):688-95.
    View in: PubMed
    Score: 0.002
  23. 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. 2014 Jan-Feb; 38(1):117-22.
    View in: PubMed
    Score: 0.002
  24. A novel analysis algorithm for potential quantitative assessment of myocardial computed tomography perfusion. Acad Radiol. 2013 Oct; 20(10):1301-5.
    View in: PubMed
    Score: 0.002
  25. Crystal analyser-based X-ray phase contrast imaging in the dark field: implementation and evaluation using excised tissue specimens. Eur Radiol. 2014 Feb; 24(2):423-33.
    View in: PubMed
    Score: 0.002
  26. Histogram analysis of lipid-core plaques in coronary computed tomographic angiography: ex vivo validation against histology. Invest Radiol. 2013 Sep; 48(9):646-53.
    View in: PubMed
    Score: 0.002
  27. The effect of iterative image reconstruction algorithms on the feasibility of automated plaque assessment in coronary CT angiography. Int J Cardiovasc Imaging. 2013 Dec; 29(8):1879-88.
    View in: PubMed
    Score: 0.002
  28. Sinogram-affirmed iterative reconstruction of low-dose chest CT: effect on image quality and radiation dose. AJR Am J Roentgenol. 2013 Aug; 201(2):W235-44.
    View in: PubMed
    Score: 0.002
  29. How to assess non-calcified plaque in CT angiography: delineation methods affect diagnostic accuracy of low-attenuation plaque by CT for lipid-core plaque in histology. Eur Heart J Cardiovasc Imaging. 2013 Nov; 14(11):1099-105.
    View in: PubMed
    Score: 0.002
  30. Evolution of coronary computed tomography radiation dose reduction at a tertiary referral center. Am J Med. 2012 Aug; 125(8):764-72.
    View in: PubMed
    Score: 0.001
  31. Comparison of hybrid and pure iterative reconstruction techniques with conventional filtered back projection: dose reduction potential in the abdomen. J Comput Assist Tomogr. 2012 May-Jun; 36(3):347-53.
    View in: PubMed
    Score: 0.001
  32. Coronary artery plaques: cardiac CT with model-based and adaptive-statistical iterative reconstruction technique. Eur J Radiol. 2012 Mar; 81(3):e363-9.
    View in: PubMed
    Score: 0.001
  33. Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques. Radiology. 2010 Nov; 257(2):373-83.
    View in: PubMed
    Score: 0.001
  34. Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique. Radiology. 2010 Jul; 256(1):261-9.
    View in: PubMed
    Score: 0.001
  35. Differentiation of cancerous lesions in excised human breast specimens using multiband attenuation profiles from ultrasonic transmission tomography. J Ultrasound Med. 2008 Mar; 27(3):435-51.
    View in: PubMed
    Score: 0.001
  36. Soft tissue differentiation using multiband signatures of high resolution ultrasonic transmission tomography. IEEE Trans Med Imaging. 2005 Mar; 24(3):399-408.
    View in: PubMed
    Score: 0.001
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.

Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.