International Journal

 

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Lee, J., Kim, S., Park, I., Eo, T., Hwang, D. (2021). Relevance CAM: Relevance weighted Class Activation Map for Visual Explanation of Convolutional Neural Networks.  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (In press)

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Jun, Y., Shin, H., Eo, T., Hwang, D. (2021). Joint Deep Model-based MR Image and Coil Sensitivity Reconstruction Network (Joint-ICNet) for Fast MRI. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (In press)

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Jun, Y., Shin, H., Eo, T., Kim, T., Hwang, D. (2021). Deep Model-based Magnetic Resonance Parameter Mapping Network (DOPAMINE) for Fast T1 Mapping Using Variable Flip Angle Method. Medical Image Analysis,  
70, 102017

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Park, Y.*, Jun, Y.*, Lee,  Y. , Han, K., An, C., Ahn, S.**, Hwang, D.**, Lee, S.(2021). Robust Performance of Deep Learning for Automatic Detection and Segmentation of Brain Metastases Using Three-dimensional Black-Blood and Three-dimensional Gradient Echo Imaging. European Radiology, ( In press )

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Shin, H., Lee, J., Eo, T., Jun, Y., Kim, S., Hwang, D. (2020). The Latest Trends in Attention Mechanisms and Their Application in Medical Imaging. Journal of the Korean Society of Radiology, 81(6), 1305-1333.

 

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Eom, J., Park, I., Kim, S., Jang, H., Hwang, D. (2021). Deep-learned Spike Representations and Sorting via an Ensemble of Auto-encoders. Neural Networks, 134, 131-142.

 

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Kim, S., Jang, H., Jang, J., Lee, Y., Hwang, D. (2020). Deep-learned Short Tau

Inversion Recovery Imaging Using Multi Contrast Magnetic Resonance Images. Magnetic Resonance in Medicine, 84(6), 2994-3008.

 

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Eo, T., Shin, H., Jun, Y., Kim, T., Hwang, D. (2020). Accelerating Cartesian MRI by Domain-Transform Manifold Learning in Phase-Encoding Direction. Medical Image Analysis, 63, 101689.

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Jang, H., Bang, K., Jang, J., Hwang, D. (2020). Dynamic Range Expansion Using Cumulative Histogram Learning for High Dynamic Range Image Generation. IEEE Access, 8, 38554-38567.

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Park, I., Eom, J., Jang, H., Kim, S., Park, S., Huh, Y., Hwang, D. (2019). Deep Learning-Based Template Matching Spike Classification for Extracellular Recordings. Applied Sciences, 10(1), 301.

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Hwang, D., Kim, D. (2019). Special Features on Intelligent Imaging and AnalysisApplied Sciences, 9(22), 4804.

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Kim, T., Kim, G., Kim, H., Yoon, H., Kim, T., Jun, Y., Shin, T., Kang, S., Cheon, J., Hwang, D., Min, B., Shim, W. (2019). Megahertz-wave-transmitting conducting polymer electrode for device-to-device integration. Nature Communications, 10(1), 653.

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Jun, Y., Eo, T., Shin, H., Kim, T., Lee, H., Hwang, D. (2019). Parallel Imaging in Time-of-Flight Magnetic Resonance Angiography Using Deep Multi-Stream Convolutional Neural Networks. Magnetic Resonance in Medicine, 81(6), 3840-3853.

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Lee, Y., Kim, S., Suh, J., Hwang, D. (2018). Learning Radiologist’s Step-by-Step Skill for Cervical Spinal Injury Examination: Line drawing, Prevertebral Soft Tissue Thickness Measurement, and Detection of the Swelling in Radiographs. IEEE Access, 6, 55492-55500.

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Jang, H., Bang, K., Jang, J., Hwang, D. (2018). Inverse Tone Mapping Operator Using Sequential Deep Neural Networks Based on Human Visual System. IEEE Access, 6, 52058-52072.

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Kim, S., Bae, W., Masuda, K., Chung, C., and Hwang, D. (2018). Fine-Grain Segmentation of the Intervertebral Discs from MR Spine Images Using Deep Convolutional Neural Networks: BSU-Net. Applied Sciences, 8(9), 1656.

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Jang, J., Jang, H., Eo, T., Bang, K., and Hwang, D. (2018). No-reference Automatic Quality Assessment for Colorfulness-Adjusted, Contrast-Adjusted, and Sharpness-Adjusted Images Using High-Dynamic-Range-Derived Features. Applied Sciences, 8(9), 1688.

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Kim, S., Bae, W., Masuda, K., Chung, C., Hwang, D. (2018). Semi-Automatic Segmentation of Vertebral Bodies in MR images of Human Lumbar Spines. Applied Sciences. 8(9), 1586. 

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Oh, D., Kim, S., Park, D., Choi, S., Song, H., Choi, Y., Moon, S., Baek, J., Hwang, D. (2018). Correction of severe beam-hardening artifacts via a high-order linearization function using a prior-image-based parameter selection methodMedical Physics, 45(9), 4133-4144.

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Jun, Y., Eo, T., Kim, T., Shin, H., Hwang, D.*, Bae, S., Park, Y., Lee, H., Choi, B., Ahn, S. (2018). Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors. Scientific Reports, 8: 9450.

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Eo, T., Jun, Y., Kim, T., Jang, J., Lee, H., & Hwang, D. (2018). KIKI-net: Cross-Domain Convolutional Neural Networks for Reconstructing Undersampled Magnetic Resonance Images. Magnetic Resonance in Medicine, 80(5), 2188-2201.

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Jang, J., Bang, K., Jang, H., & Hwang, D. (2018). Quality Evaluation of No-reference MR Images Using Multidirectional Filters and Image Statistics. Magnetic Resonance in Medicine, 80(3), 914-924.

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Lee, Y., & Hwang, D. (2018). Periodicity-based nonlocal-means denoising method for electrocardiography in low SNR non-white noisy conditions. Biomedical Signal Processing and Control, 39, 284-293.

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