[C94]Multisource C-arm CT: Initial Results with a 2 x 2 Carbon Nanotube Source Array
Hojin Jung, Jongduk Baek
CT Meeting, 2026 · Oral Presentation
Conference
2026
[C93]Noise and Anatomy Adaptive Convolution for Efficient Low-Dose CT Denoising
Minwoo Yu, Jongduk Baek, Adam Wang
CT Meeting, 2026
[C92]Two-Stage Cascaded Caries Detection on Panoramic X-Ray via Slicing-Aided Hyper Inference
Subin Park, Yoonha Eo, Jongduk Baek
CT Meeting, 2026
[C91]SynthCaries: Dental Caries Generation on Panoramic Radiograph using Diffusion
Yoonha Eo, Eunmin Lee, Jongduk Baek
CT Meeting, 2026
[C90]Training cone-beam artifact reduction networks with only artifact-contaminated CBCT images
Minah Han, Jongduk Baek
SPIE Medical Imaging, 2026
[C89]A multi-stage deep learning framework for correcting combined metal and truncation artifacts in half-detector CBCT
Junhyun Ahn, Jongduk Baek
SPIE Medical Imaging, 2026
[C88]SAVI: Slope-aware sparse-view sinogram interpolation
Kyungseo Kwon, Minwoo Yu, Junhyun Ahn, Hwanhui Jo, Jongduk Baek
SPIE Medical Imaging, 2026
2025
[C87]Emulating Human Perception of Low-Dose CT Image Quality via Deep Generative Models
Jooho Lee, Jongduk Baek, Adam S. Wang
AAPM, 2025 · Oral Presentation
[C86]Fully Automatic Pipelines for Anatomical ROI Detection and Exposure Index Calculation in X-Ray Imaging: Foundation Model-Based Frameworks for Dose Standardization
Yoonha Eo, Jongduk Baek
AAPM, 2025
[C85]Noise Canceling Approach for C-Arm X-Ray Fluoroscopy: Solution for Dynamic Imaging Scenarios
Yoonha Eo, Jongduk Baek
Fully3D, 2025
[C84]A method to reduce truncation artifacts in dental CT with an offset detector with sinogram domain learning
Taijun Kang, Seongjun Kim, Jongduk Baek
Fully3D, 2025
[C83]Radiologist-Guided Fine-Tuning of a CT Image Restoration Model
Minwoo Yu, Seungjun Lee, Yejin Chun, Jongduk Baek
Fully3D, 2025
[C82]Standardization of lung CT number using solid references in COPDgene2 phantom
Hoondong Song, Hanjoo Jang, Jongduk Baek
Fully3D, 2025
[C81]A representation-based method for continuous CT image reconstruction
Minwoo Yu, Jongduk Baek
SPIE Medical Imaging, 2025 · Oral Presentation
[C80]Early step skipping score-based generative model for low-dose CT denoising
Hojin Jung, Jongduk Baek
SPIE Medical Imaging, 2025
[C79]Self-supervised metal artifacts reduction with a continuous constraint along the z-axis
Junhyun Ahn, Sungil Choi, Seungwon Choi, Chulkyu Park, Jueon Park, Chul Lee, Jongduk Baek
SPIE Medical Imaging, 2025
[C78]Dose-aware adaptive denoising network for low-dose CT
Seongjun Kim, Byeongjoon Kim, Jongduk Baek
SPIE Medical Imaging, 2025
[C77]Regularizing neural fields for 3D computed tomographic imaging from sparse projections
Jooho Lee, Byeongjoon Kim, Jongduk Baek
SPIE Medical Imaging, 2025
2024
[C76]Neural attenuation fields for metal artifact reduction in dental CT
Jooho Lee, Junhyun Ahn, Jongduk Baek
SPIE Medical Imaging, 2024 · Oral Presentation
[C75]Understanding the generalizability of a convolutional neural network-based model observer for breast tomosynthesis images with different volume glandular fractions
Hanjoo Jang, Jongduk Baek
SPIE Medical Imaging, 2024 · Oral Presentation
[C74]Patient-specific data augmentation method to improve the training efficiency of convolutional neural network for metal artifact reduction with a single patient dental CT volume
Junhyun Ahn, Jongduk Baek
SPIE Medical Imaging, 2024
[C73]Feasibility study of using masked auto-encoder for a streak artifact reduction in sparse view CT
Gihun Kim, Jongduk Baek
SPIE Medical Imaging, 2024
[C72]A method to generate patient CT noise for deep learning network training
Minah Han, Jongduk Baek
SPIE Medical Imaging, 2024
2023
[C71]Limited-angle CT reconstruction using implicit neural representation with learned initialization
Jooho Lee, Jongduk Baek
Fully3D, 2023
[C70]An investigation on the detection task performance of deep learning based streak artifacts reduction methods
Hojin Jung, Minwoo Yu, Jongduk Baek
Fully3D, 2023
2022
[C69]Sparsier2Sparse: Weakly-supervised learning for streak artifacts reduction with unpaired sparse view CT data
S. Kim, B. Kim, and J. Baek
CT Meeting, 2022 · Oral Presentation
[C68]A hybrid domain processing for CT image super-resolution via sinogram upsampling network with modulated periodic activations
M. Yu, M. Han, and J. Baek
SPIE Medical Imaging, 2022
[C67]Streak artifacts reduction algorithm using an implicit neural representation in sparse-view CT
B. Kim, H. Shim, and J. Baek
SPIE Medical Imaging, 2022
[C66]A new method to reduce helical artifacts in the reconstructed image from direct filtered backprojection
S. Choi and J. Baek
SPIE Medical Imaging, 2022
[C65]Low dose CT denoising via CNN trained using images with activation map
M. Han and J. Baek
SPIE Medical Imaging, 2022
[C64]A sequential approach using convolutional neural networks for motion artifacts reduction with a fast CT scan mode
S. Moon, B. Kim, Y. Choi, and J. Baek
SPIE Medical Imaging, 2022
2021
[C63]A method to estimate a fan beam CT NPS using two basis functions with a limited number of noise realizations
H. Jang, M. Koh, and J. Baek
AAPM, 2021 · Oral Presentation
[C62]Convolutional neural network based metal artifact correction for sparse view dental CT imaging
S. Kim, J. Ahn, and J. Baek
AAPM, 2021 · Oral Presentation
[C61]Super-resolution CT image via convolutional neural network with an observer loss function
M. Yu, M. Han, and J. Baek
AAPM, 2021
[C60]CNN based CT denoising with an accurate image domain noise insertion technique
B. Kim, S. E. Divel, N. J. Pelc, and J. Baek
SPIE Medical Imaging, 2021
[C59]Implementation of CNN-based multi-slice model observer for 3D cone beam CT
G. Kim and J. Baek
SPIE Medical Imaging, 2021 · Oral Presentation
[C58]A hybrid domain approach to reduce streak artifacts of sparse view CT image via convolutional neural network
S. Kim, B. Kim, and J. Baek
SPIE Medical Imaging, 2021
[C57]Convolutional neural network based metal artifact reduction method in dental CT image
J. Ahn, Y. Choi, and J. Baek
SPIE Medical Imaging, 2021
[C56]Sphere phantom approach to measure MTF of computed tomography system using convolutional autoencoder network
C. Lee and J. Baek
SPIE Medical Imaging, 2021
[C55]Denoising low dose CT using pre-trained lesion classification network
M. Han and J. Baek
SPIE Medical Imaging, 2021
2020
[C54]Training strategies of a convolutional neural network based anthropomorphic model observer for signal-known exactly and background known statistically detection tasks
B. Kim, M. Han, and J. Baek
CT Meeting, 2020 · Oral Presentation
[C53]Convolutional neural network-based anthropomorphic model observer for breast cone-beam CT images
B. Kim, M. Han, and J. Baek
SPIE Medical Imaging, 2020
[C52]A performance comparison of convolutional neural network based anthropomorphic model observer and linear model observer for signal-known-statistically detection tasks
M. Han, B. Kim, and J. Baek
SPIE Medical Imaging, 2020
[C51]Convolutional neural network based anthropomorphic model observer for breast tomosynthesis images
C. Lee and J. Baek
SPIE Medical Imaging, 2020
2019
[C50]Multislice anthropomorphic model observer for detectability evaluation on breast cone beam CT images
M. Han and J. Baek
Fully3D, 2019 · Oral Presentation
[C49]Field of view based metal artifact reduction method with the presence of data truncation
S. Choi and J. Baek
Fully3D, 2019
[C48]Investigation on lesion detectability in step-and-shoot mode and continuous mode digital tomosynthesis system with anatomical background
C. Lee and J. Baek
SPIE Medical Imaging, 2019
[C47]Multidimensional Noise Reduction in C-arm Cone-beam CT via 2D-based Landweber Iteration and 3D-based Deep Neural Networks
J. Kim, D. Choi, S. Chae, B. Kim, J. Baek, A. Maier, R. Fahrig, H. Park, J. Choi
SPIE Medical Imaging, 2019
[C46]Investigation on slice direction dependent denoising performance of convolutional neural network in cone beam CT images
E. Lee, B. Kim, J. Baek
SPIE Medical Imaging, 2019
[C45]Implementation of an ideal observer model using convolutional neural network for breast CT images
G. Kim, M. Han, H. Shim, J. Baek
SPIE Medical Imaging, 2019 · Oral Presentation
[C44]Performance comparison of water phantom based flat field correction methods for photon counting spectral CT images: Experimental results
D. Kim and J. Baek
SPIE Medical Imaging, 2019
[C43]Performance comparison of convolutional neural network based denoising in low dose CT images for various loss functions
B. Kim, M. Han, H. Shim, J. Baek
SPIE Medical Imaging, 2019
2018
[C42]Comparison of flat field correction methods for photon-counting spectral CT images
D. Kim and J. Baek
IEEE MIC, 2018
[C41]Image Quality Enhancement of Digital Breast Tomosynthesis Images by Deblurring with Deep Residual Convolutional Neural Networks
Y. Choi, H. Shim, and J. Baek
IEEE MIC, 2018
[C40]3-D MTF Estimation Using Sphere Phantoms for Cone-Beam Computed Tomography Systems
H. Song, C. Lee and J. Baek
IEEE MIC, 2018
[C39]Performance comparison of deep learning based denoising techniques in low-dose CT images
B. Kim, H. Shim, and J. Baek
CT Meeting, 2018
[C38]A multi pass approach to reduce cone beam artifacts in a circular orbit cone beam CT system
C. Han and J. Baek
CT Meeting, 2018
[C37]Feasibility study of deep convolutional generative adversarial networks to generate mammography images
G. Kim, H. Shim, and J. Baek
SPIE Medical Imaging, 2018
[C36]Lesion detection performance of cone beam CT images with anatomical noise background: single slice vs multi slice human and model observer study
M. Han, H. Jang and J. Baek
SPIE Medical Imaging, 2018 · Oral Presentation
[C35]A deeper convolutional neural network for denoising low dose CT images
B. Kim, H. Shim and J. Baek
SPIE Medical Imaging, 2018
[C34]A new method to reduce cone beam artifacts by optimal combination of FDK and TV-IR images
S. Choi and J. Baek
SPIE Medical Imaging, 2018
[C33]In-plane MTF measurement using sphere phantoms for step-and-shoot mode and continuous mode digital tomosynthesis systems
C. Lee and J. Baek
SPIE Medical Imaging, 2018
2017
[C32]Comparison of lesion detectability with single slice and multiple slice images in breast cone beam computed tomography
M. Han and J. Baek
Fully3D, 2017 · Oral Presentation
[C31]Detectability of multiple slice breast cone beam computed tomography images
M. Han, B. Kim, and J. Baek
AAPM, 2017
[C30]Investigation on location dependent detectability in cone beam CT images with uniform and anatomical backgrounds
M. Han and J. Baek
SPIE Medical Imaging, 2017 · Oral Presentation
[C29]Dual energy approach for cone beam artifacts correction
C. Han, S. Choi, C. Lee, and J. Baek
SPIE Medical Imaging, 2017
[C28]Comparison of detectability in step-and-shoot mode and continuous mode digital tomosynthesis systems
C. Lee, M. Han, and J. Baek
SPIE Medical Imaging, 2017
[C27]The effect of a finite focal spot size on location dependent detectability in a fan beam CT system
B. Kim and J. Baek
SPIE Medical Imaging, 2017
2016
[C26]A method to reduce information loss in JPEG compressed medical images using Richardson-Lucy deconvolution
Y. Choi, M. Han, and J. Baek
AAPM, 2016
[C25]Investigation on detectability of cone beam CT images with anatomical background
M. Han and J. Baek
GRC Image Science, 2016
[C24]Effect of anatomical backgrounds on detectability in volumetric cone beam CT images
M. Han, S. Park, and J. Baek
SPIE Medical Imaging, 2016
[C23]Investigation on location-dependent detectability of a small mass for digital breast tomosynthesis evaluation
C. Lee, S. Park, and J. Baek
SPIE Medical Imaging, 2016
[C22]Metal artifact reduction algorithm based on the data-adapted moving least squares using minimum estimated sinogram
H. Nam and J. Baek
CT Meeting, 2016
2015
[C21]Investigation on detectability of a small target for different slice direction of a volumetric cone beam CT image
C. Lee, M. Han, and J. Baek
AAPM, 2015
[C20]Directional MTF measurement using sphere phantoms for a digital breast tomosynthesis system
C. Lee and J. Baek
SPIE Medical Imaging, 2015
[C19]Comparison of cone beam artifacts reduction: two pass algorithm vs TV-based CS algorithm
S. Choi and J. Baek
SPIE Medical Imaging, 2015
[C18]Investigation on viewing direction dependent detectability in a reconstructed 3D volume for a cone beam CT system
J. Park, C. Lee, and J. Baek
SPIE Medical Imaging, 2015
[C17]3D motion artifact compensation in CT image with depth camera
Y. Ko, J. Baek, and H. Shim
IS&T/SPIE Medical Imaging, 2015
[C16]A New Channel Design of Channelized Hotelling Observer and Internal Noise Optimization to Match Human Observer
M. Han and J. Baek
Fully3D, 2015
[C15]Metal artifact reduction algorithm using directional interpolation by sinogram decomposed derivatives
H. Nam and J. Baek
IEEE MIC/NSS, 2015
2014
[C14]Comparison of deconvolution techniques to measure directional MTF of FDK reconstruction
C. Lee, Y. Ko, J. Park, and J. Baek
SPIE Medical Imaging, 2014
[C13]Investigations of internal noise levels for different target sizes, contrasts, and noise structures
M. Han, S. Choi, and J. Baek
SPIE Medical Imaging, 2014
before 2014
[C12]Effects of Sparse Sampling Schemes on Image Quality in Low-Dose CT
S. Abbas, T. Lee, H. Chung, T. H. Chung, J. Baek, and S. Cho
AAPM, 2013
[C11]Initial results with a multi-source inverse-geometry CT system
J. Baek, B. De Man, J. Uribe, D. Harrison, J. Reynolds, B. Neculaes, L. Inzinna, and A. Caiafa
SPIE Medical Imaging, 2012
[C10]Data normalization method for a multi-source inverse geometry CT system
J. Baek and N. J. Pelc
SPIE Medical Imaging, 2012
[C9]Frequency-combined extended 3D reconstruction for multiple circular cone-beam CT scans
G. Rainer, J. Baek, N. J. Pelc, and M. Kachelriess
IEEE MIC, 2011
[C8]Use of sphere phantoms to measure the 3D MTF of FDK reconstructions
J. Baek and N. J. Pelc
SPIE Medical Imaging, 2011
[C7]Multisource Inverse-Geometry CT-Prototype System Integration
J. Uribe, J. Reynolds, L. Inzinna, R. Longtin, D. Harrison, B. De Man, B. Neculaes, A. Caiafa, W. Waters, K. Frutschy, R. Senzig, J. Baek, and N. J. Pelc
IEEE MIC, 2010
[C6]Multisource inverse-geometry CT: From system concept to research prototype
B. De Man, A. Caiafa, C. Yang, K. Frutschy, D. Harrison, L. Inzinna, R. Longtin, B. Neculaes, J. Reynolds, J. Roy, J. Short, J. Uribe, W. Waters, Y. Zhu, Z. Xi, Z. Yun, B. Senzig, J. Baek, and N. Pelc
IEEE MIC, 2009
[C5]Analytical construction of 3D NPS for a cone beam CT system
J. Baek and N. J. Pelc
SPIE Medical Imaging, 2009
[C4]SNR efficient 3D reconstruction algorithm for multi-source inverse geometry CT system
J. Baek and N. J. Pelc
SPIE Medical Imaging, 2009
[C3]Analytical derivation of the noise power spectrum for a fan beam system
J. Baek and N. J. Pelc
AAPM, 2008
[C2]A new reconstruction method to improve SNR for an inverse geometry CT system
J. Baek and N. J. Pelc
SPIE Medical Imaging, 2008
[C1]Two-dimensional reconstruction algorithm of an inverse-geometry volumetric CT system
J. Baek and N. J. Pelc
SPIE Medical Imaging, 2007