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International Journal

Journals

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M3T: three-dimensional Medical image classifier using Multi-plane and Multi-slice Transformer,  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

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Importance of CT image normalization in radiomics analysis: prediction of 3-year recurrence-free survival in non-small cell lung cancer. European Radiology, 2022.

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Graphical Abstract-BlochGAN.tif

[BlochGAN]

Fat-saturated Image Generation from Multi-contrast MRIs Using Generative Adversarial Networks with Bloch Equation-based Autoencoder Regularization. Medical Image Analysis, Volume 73, October 2021, 102198

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Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction. -with Facebook AI & NYU.  IEEE Transactions on Medical Imaging, (In press)

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Relevance CAM Relevance weighted Class A

Lee, J., Kim, S., Park, I., Eo, T., Hwang, D. (2021). Relevance-CAM: Your Model Already Knows Where to Look.  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, pp. 14944-14953

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Quantitative analysis of the mouth opening movement of temporomandibular joint disorder patients according to disc position using computer vision: a pilot study. QUANTITATIVE IMAGING IN MEDICINE AND SURGERY , 2021.

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Joint Deep Model-based MR Image and Coil

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. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, pp. 5270-5279

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Deep Model-based Magnetic Resonance Para

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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Deep-learned Short Tau Inversion Recover

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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Accelerating Cartesian MRI by Domain-Tra

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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Dynamic Range Expansion Using Cumulative

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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Deep Learning-Based Template Matching Sp

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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Special Features on Intelligence Imaging

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

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Megahertz-wave-transmitting conducting p

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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Parallel Imaging in Time-of-Flight Magne

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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Learning_Radiologist’s_Step-by-Step_Skil

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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Inverse Tone Mapping Operator Using Sequ

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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Fine-grain segmentation of the intervert

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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No-reference automatic quality assessmen

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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Semi-Automatic Segmentation of Vertebral

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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Correction of severe beam-hardening arti

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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Deep-learned 3D black-blood imaging usin

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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KIKI-net Cross-Domain Convolutional Neur

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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Quality Evaluation of No-reference MR Im

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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Periodicity-based nonlocal-means denoisi

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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Small-scale_noise-like_moiré_pattern_cau

Kim, Y., Oh, D., & Hwang, D. (2017). Small-scale noise-like moiré pattern caused by detector sensitivity inhomogeneity in computed tomography. Optics Express, 25(22), 27127-27145.

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Gait phase detection from sciatic nerve

Song, K. I., Chu, J. U., Park, S. E., Hwang, D., & Youn, I. (2017). Ankle-Angle Estimation from Blind Source Separated Afferent Activity in the Sciatic Nerve for Closed-Loop Functional Neuromuscular Stimulation System. IEEE Transactions on Biomedical Engineering, 64(4), 834-843.

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High-SNR multiple T2()-contrast magnetic

Eo, T., Kim, T., Jun, Y., Lee, H., Ahn, S. S., Kim, D. H., & Hwang, D. (2017). High‐SNR multiple T2 (*)‐contrast magnetic resonance imaging using a robust denoising method based on tissue characteristics. Journal of Magnetic Resonance Imaging, 45(6), 1835-1845.

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Quantitative magnetic resonance imaging

Hwang, D., Kim, S., Abeydeera, N. A., Statum, S., Masuda, K., Chung, C. B., ... & Bae, W. C. (2016). Quantitative magnetic resonance imaging of the lumbar intervertebral discs. Quantitative Imaging in Medicine and Surgery, 6(6), 744-755.

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Metal artifact reduction for polychromat

Park, H. S., Hwang, D., & Seo, J. K. (2016). Metal artifact reduction for polychromatic x-ray CT based on a beam-hardening corrector. IEEE transactions on medical imaging, 35(2), 480-487. 

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Murmur-adaptive compression technique fo

Kim, S., & Hwang, D. (2015). Murmur-adaptive compression technique for phonocardiogram signalsElectronics Letters, 52(3), 183-184.

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Improved estimation of myelin water frac

Nam, Y., Lee, J., Hwang, D., & Kim, D. H. (2015). Improved estimation of myelin water fraction using complex model fittingNeuroImage, 116, 214-221.

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A time-course study of behavioral and el

Park, S. E., Song, K. I., Suh, J. K. F., Hwang, D., & Youn, I. (2015). A time-course study of behavioral and electrophysiological characteristics in a mouse model of different stages of Parkinson's disease using 6-hydroxydopamine. Behavioural brain research, 284, 153-157.

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Susceptibility map-weighted imaging (SMW

Gho, S. M., Liu, C., Li, W., Jang, U., Kim, E. Y., Hwang, D., & Kim, D. H. (2014). Susceptibility map‐weighted imaging (SMWI) for neuroimaging. Magnetic resonance in medicine, 72(2), 337-346.

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Ring artifact correction using detector

Kim, Y., Baek, J., & Hwang, D. (2014). Ring artifact correction using detector line-ratios in computed tomography. Optics express, 22(11), 13380-13392.

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Special issue on medical imaging_image.P

Hwang, D., & Zeng, G. L. (2014). Special issue on medical imaging. Biomedical Engineering Letters, 4(1), 1-2.

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Feedback control of electrode offset vol

Chu, J. U., Song, K. I., Shon, A., Han, S., Lee, S. H., Kang, J. Y., ... & Youn, I. (2013). Feedback control of electrode offset voltage during functional electrical stimulation. Journal of neuroscience methods, 218(1), 55-71.

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A tissue-relaxation-dependent neighborin

Kwon, O. I., Woo, E. J., Du, Y. P., & Hwang, D. (2013). A tissue-relaxation-dependent neighboring method for robust mapping of the myelin water fraction. NeuroImage, 74, 12-21.

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Gait phase detection from sciatic nerve

Chu, J. U., Song, K. I., Han, S., Lee, S. H., Kang, J. Y., Hwang, D., ... & Youn, I. (2013). Gait phase detection from sciatic nerve recordings in functional electrical stimulation systems for foot drop correction. Physiological measurement, 34(5), 541.

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Improvement of the SNR and resolution of

Jang, U., Nam, Y., Kim, D. H., & Hwang, D. (2013). Improvement of the SNR and resolution of susceptibility-weighted venography by model-based multi-echo denoising. Neuroimage, 70, 308-316.

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Noise reduction in magnetic resonance im

Kang, B., Choi, O., Kim, J. D., & Hwang, D. (2013). Noise reduction in magnetic resonance images using adaptive non-local means filtering. Electronics Letters, 49(5), 324-326.

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Improvement of signal-to-interference ra

Chu, J. U., Song, K. I., Han, S., Lee, S. H., Kim, J., Kang, J. Y., ... & Youn, I. (2012). Improvement of signal-to-interference ratio and signal-to-noise ratio in nerve cuff electrode systems. Physiological measurement, 33(6), 943.

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Toothbrushing region detection using thr

Lee, Y. J., Lee, P. J., Kim, K. S., Park, W., Kim, K. D., Hwang, D., & Lee, J. W. (2012). Toothbrushing region detection using three-axis accelerometer and magnetic sensor. IEEE Transactions on Biomedical Engineering, 59(3), 872-881.

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High‐quality_multiple_T2_()_contrast_MR_

Jang, U., & Hwang, D. (2012). High‐quality multiple T2 (*) contrast MR images from low‐quality multi‐echo images using temporal‐domain denoising methods. Medical physics, 39(1), 468-474.

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SPECT_reconstruction_with_sub‐sinogram_a

Hwang, D., Lee, J. W., & Zeng, G. L. (2011). SPECT reconstruction with sub‐sinogram acquisitions. International Journal of Imaging Systems and Technology, 21(3), 247-252.

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Robust mapping of the myelin water fract

Hwang, D., Chung, H., Nam, Y., Du, Y. P., & Jang, U. (2011). Robust mapping of the myelin water fraction in the presence of noise: synergic combination of anisotropic diffusion filter and spatially regularized nonnegative least squares algorithm. Journal of Magnetic Resonance Imaging, 34(1), 189-195.

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In vivo multi-slice mapping of myelin wa

Hwang, D., Kim, D. H., & Du, Y. P. (2010). In vivo multi-slice mapping of myelin water content using T2* decay. NeuroImage, 52(1), 198-204.

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Improved_myelin_water_quantification_usi

Hwang, D., & Du, Y. P. (2009). Improved myelin water quantification using spatially regularized non‐negative least squares algorithm. Journal of Magnetic Resonance Imaging, 30(1), 203-208.

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Fast multislice mapping of the myelin wa

Du, Y. P., Chu, R., Hwang, D., Brown, M. S., Kleinschmidt‐DeMasters, B. K., Singel, D., & Simon, J. H. (2007). Fast multislice mapping of the myelin water fraction using multicompartment analysis of T decay at 3T: A preliminary postmortem study. Magnetic Resonance in Medicine, 58(5), 865-870.

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Nagarajan, S. S., Portniaguine, O., Hwang, D., Johnson, C., & Sekihara, K. (2006). Controlled support MEG imaging. NeuroImage, 33(3), 878-885.

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Convergence study of an accelerated ML-E

Hwang, D., & Zeng, G. L. (2005). Convergence study of an accelerated ML-EM algorithm using bigger step size. Physics in medicine and biology, 51(2), 237.

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Reduction of noise amplification in SPEC

Hwang, D., & Zeng, G. L. (2005). Reduction of noise amplification in SPECT using smaller detector bin sizeIEEE transactions on nuclear science, 52(5), 1417-1427.

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A new simple iterative reconstruction al

Hwang, D., & Zeng, G. L. (2005). A new simple iterative reconstruction algorithm for SPECT transmission measurement. Medical physics, 32(7), 2312-2319.

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Journals
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©2020 Medical Artificial Intelligence Laboratory

at Yonsei University

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