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[JCAT] Choi, J. W., Lee, S. Y., Kim, J. H., Jin, H., Lee, J., Choi, Y. H., ... & Park, J. H. (2018). Iterative Metallic Artifact Reduction for In-Plane Gonadal Shielding During Computed Tomographic Venography of Young Males. Journal of Computer Assisted Tomography, 42(2), 269-276.
http://www.ncbi.nlm.nih.gov/pubmed/28937486


[Acad Radiol.] Storz, C., Kolb, M., Kim, J. H., Weiss, J., Kunz, W. G., Nikolaou, K., ... & Othman, A. E. (2018). Impact of Radiation Dose Reduction in Abdominal Computed Tomography on Diagnostic Accuracy and Diagnostic Performance in Patients with Suspected Appendicitis: An Intraindividual Comparison. Academic Radiology, 25(3), 309-316.
http://www.ncbi.nlm.nih.gov/pubmed/29174188


[SPIE] Ahn, C. K., Yang, Z., Heo, C., Jin, H., Park, B., & Kim, J. H. (2018, March). A Deep Learning-Enabled Iterative Reconstruction of Ultra-Low-Dose CT: Use of Synthetic Sinogram-based Noise Simulation Technique. In SPIE Medical Imaging 2018: Physics of Medical Imaging (Vol. 10573, p.1057335). International Society for Optics and Photonics.
http://dx.doi.org/10.1117/12.2294013


[SPIE] Jin, H., Heo, C., & Kim, J. H. (2018, February). Impact of deep learning on the normalization of reconstruction kernel effects in imaging biomarker quantification: a pilot study in CT emphysema. In Medical Imaging 2018: Computer-Aided Diagnosis (Vol. 10575, p. 105753L). International Society for Optics and Photonics.
https://doi.org/10.1117/12.2295010

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