[Acad Radiol.] Storz, C., Kolb, M., Kim, J. H., Weiss, J., Kunz, W. G., Nikolaou, K., ... & Othman, A. E. (2017). 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.

[JCAT] Choi, J. W., Lee, S. Y., Kim, J. H., Jin, H., Lee, J., Choi, Y. H., ... & Park, J. H. (2017). Iterative Metallic Artifact Reduction for In-Plane Gonadal Shielding During Computed Tomographic Venography of Young Males. Journal of Computer Assisted Tomography,

[KJR] Lee, M., Woo, B., Kuo, M. D., Jamshidi, N., & Kim, J. H. (2017). Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software. Korean Journal of Radiology, 18(3), 498-509.

[SPIE] Ahn, C. K., Heo, C., Jin, H., & Kim, J. H. (2017, March). A Novel Deep Learning-based Approach to High Accuracy Breast Density Estimation in Digital Mammography. In SPIE Medical Imaging (pp. 101342O-101342O). International Society for Optics and Photonics.

[IFMIA] Ahn, C., Park, B., Jin, H., Heo, C., Yang, Z., Lee, J., & Kim, J. H. (2017). A Deep Learning Approach to Automated Mammographic Breast Density Estimation.



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