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[MICCAI] Chun, M., & Kim, J. H. (2014, September). Combined Homogeneous Region Localization and Automated Evaluation of Radiation Dose Dependent Contrast-to-Noise Ratio in Dual Energy Abdominal CT. In International MICCAI Workshop on Computational and Clinical Challenges in Abdominal Imaging (pp. 278-286). Springer International Publishing.
http://dx.doi.org/10.1007/978-3-319-13692-9_27


[MedPhys] Kim, Y., Hong, B. W., Kim, S. J., & Kim, J. H. (2014). A population-based tissue probability map-driven level set method for fully automated mammographic density estimations. Medical physics, 41(7), 071905.
http://www.ncbi.nlm.nih.gov/pubmed/24989383


[AAPM] Jin, H., & Kim, J. (2014). SU-EI-31: Image-Based Kernel Conversion Technique Normalizes the Reconstruction Kernel Effects in the Measurement of Emphysema Index in CT. Medical Physics, 41(6), 136-137.
http://dx.doi.org/10.1118/1.4887979


[AAPM] Chun, M., & Kim, J. (2014). WE-D-18A-07: Development and Evaluation of Automated Noise Measurement Technique in CT Images. Medical physics, 41(6), 499-499.
http://dx.doi.org/10.1118/1.4889416


[IWDM] Kim, Y., & Kim, J. H. (2014, June). Reliability of Breast Density Estimation in Follow-Up Mammograms: Repeatability and Reproducibility of a Fully Automated Areal Percent Density Method. In International Workshop on Digital Mammography (pp. 304-311). Springer International Publishing.
https://dx.doi.org/10.1007/978-3-319-07887-8_43


[SPIE] Lee, M., Kim, J. H., Park, M. H., Kim, Y. H., Seong, Y. K., Cho, B. H., & Woo, K. G. (2014, March). Computer-aided classification of liver tumors in 3D ultrasound images with combined deformable model segmentation and support vector machine. In SPIE Medical Imaging (pp. 90341N-90341N). International Society for Optics and Photonics.
http://dx.doi.org/10.1117/12.2043427


[SPIE] Heo, C. Y., & Kim, J. H. (2014, March). Comparison of biophysical factors influencing on emphysema quantification with low-dose CT. In SPIE Medical Imaging (pp. 90352E-90352E). International Society for Optics and Photonics.
http://dx.doi.org/10.1117/12.2043894


[MedPhys] Kim, C. W., & Kim, J. H. (2014). Realistic simulation of reduced-dose CT with noise modeling and sinogram synthesis using DICOM CT images. Medical physics, 41(1), 011901.
http://www.ncbi.nlm.nih.gov/pubmed/24387509


[RSNA] Jin, H., & Kim, J. (2014). SU‐E‐I‐31: Image‐Based Kernel Conversion Technique Normalizes the Reconstruction Kernel Effects in the Measurement of Emphysema Index in CT. Medical Physics, 41(6), 136-137.
https://dx.doi.org/10.1118/1.4887979

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