스탠퍼드대학교 전기공학 박사 (2014)
스탠퍼드대학교 통계학 석사 (2012)
스탠퍼드대학교 전기공학 석사 (2008)
서울대학교 전기컴퓨터공학 석사 (2006)
서울대학교 전기공학 학사 (2004)

조교수, 서울과학기술대학교 (2023.9-현재)
선임연구원, 한국과학기술연구원 (2017.3-2023.8)
전문연구원, 삼성전자 종합기술원 (2014.4-2017.2)

◾ K Choi, SH Kim, S Kim, “Self-Supervised Learning in Projection Domain for Low-Dose Cone-Beam CT”, Medical Physics, 2023

◾ K Choi, S Kim, J Lim, “Self-Supervised Inter- and Intra-Slice Correlation Learning for Low-Dose CT Image Restoration without Ground Truth", Expert Systems with Applications, 2022.

◾ K Choi, S Kim, J Lim, “StatNet: Statistical Image Restoration for Low-Dose CT using Deep Learning”, IEEE Journal of Selected Topics in Signal Processing, 2020.

◾ K Choi, R Li, H Nam, L Xing, “A Fourier-based Compressed Sensing Technique for Accelerated CT Image Reconstruction using First-Order Methods”, Physics in Medicine and Biology, 2014.

◾ K Choi, J Wang, L Zhu, T-S Suh, S Boyd, L Xing, “Compressed Sensing based Cone-Beam Computed Tomography Reconstruction with a First-Order Method”, Medical Physics, 2010.

◾ Artificial Intelligence Model for Detection of Colorectal Cancer on Routine Abdominopelvic CT Examinations: A Training and External-Testing Study, American Journal of Roentgenology, 2025.

◾ Self-Supervised Learning-based CT Image Denoising and Reconstruction: A Review, Biomedical Engineering Letters, 2024. (invited paper)

◾ Self-Supervised Learning in Projection Domain for Low-Dose Cone-Beam CT, Medical Physics, 2023.

◾ Self-Supervised Inter- and Intra-Slice Correlation Learning for Low-Dose CT Image Restoration without Ground Truth, Expert Systems with Applications, 2022.

◾ Prediction of the histology of colorectal neoplasm in white light colonoscopic images using deep learning algorithms, Scientic Reports, 2021.

◾ StatNet: Statistical Image Restoration for Low-Dose CT using Deep Learning”, IEEE Journal of Selected Topics in Signal Processing, 2020.

◾ A Subband-Specic Deconvolution Model for MTF Improvement in CT, Journal of Healthcare Engineering, 2017.

◾ A Distance-Driven Deconvolution Method for CT Image-Resolution Improvement, Journal of the Korean Physical Society, 2016.

◾ A Preliminary Study of an Image Synthesis Method to Simulate the Change in Incident X-ray Spectrum using Thickness Information, Journal of the Korean Physical Society, 2016.

◾ A Fourier-based Compressed Sensing Technique for Accelerated CT Image Reconstruction using First-Order Methods, Physics in Medicine and Biology, 2014.

◾ First Study of On-Treatment Volumetric Imaging During Respiratory Gated VMAT, Medical Physics, 2013. (Highlighted as Editor's Pick)

◾ Enhancement of Four-Dimensional Cone-Beam Computed Tomography by Compressed Sensing with Bregman Iteration, Journal of X-Ray Science and Technology, 2013.

◾ Total-Variation Regularization based Inverse Planning for Intensity Modulated Arc Therapy, Technology of Cancer Research & Treatment, 2012.

◾ Compressed Sensing based Cone-Beam Computed Tomography Reconstruction with a First-Order Method, Medical Physics, 2010.

◾ K Choi, “A Comparative Study between Image and Projection-Domain Self-Supervised Denoising for Ultra Low-Dose CBCT”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society
(EMBC), 2022.

◾ Y Kim, S Park, H Kim, SS Kim, JS Lim, S Kim, K Choi, H Seo, “A Bounding-Box Regression Model for Colorectal Tumor Detection in CT Images Via Two Contrary Networks”, Annual International Conference
of the IEEE Engineering in Medicine and Biology Society (EMBC), 2022.

◾ K Choi, “Self-supervised Projection Denoising for Low-Dose Cone-Beam CT”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2021.

◾ J Kwon, K Choi, “Weakly Supervised Attention Map Training for Histological Localization of Colonoscopy Images”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2021.

◾ K Choi, SJ Choi, ES Kim, “Computer-Aided diagonosis for colorectal cancer using deep learning with visual explanations”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2020.

◾ K Choi, S Kim, “Statistical Image Restoration for Low-Dose CT using Convolutional Neural Networks”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2020.

◾ J Kwon, K Choi, “Trainable multi-contrast windowing for liver CT segmentation”, IEEE International Conference on Big Data and Smart Computing (BigComp), 2020. (Best Paper Award)

◾ K Choi, M Vania, S Kim, “Semi-Supervised Learning for Low-Dose CT Image Restoration with Hierarchical Deep Generative Adversarial Network (HD-GAN)”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019.

◾ K Choi, S Kim, J Lim “Real-time image reconstruction for low-dose CT using deep convolutional generative adversarial networks (GANs)”, SPIE Medical Imaging, 2018.

◾ K Choi, J Wang, L Zhu, T Suh, S Boyd, L Xing, “Compressed Sensing with a First-Order Method for Low-Dose Cone-Beam CT Reconstruction”, International Conference on the Use of Computers in Radiation Therapy (ICCR), 2010. (oral presentation)

◾ K Choi and S Choi, “CLPC: Cross-Layer Product Code for Video Multicast over WLAN”, MediaWiN Workshop of European Wireless, 2006. (invited paper)

◾ L Xing, J Qian, K Choi, T-S Suh, “Three- and Four-dimensional Morphological Imaging for Adaptive Radiation Therapy Planning”, chapter 2 in Adaptive Radiation Therapy, CRC Press, 2011.

◾ S Choi and K Choi, “Reliable Multicast for Wireless Local Area Networks,” chapter 4 in Resource, Mobility and Security Management in Wireless Networks and Mobile Communications, CRC Press, 2006.

◾ Image processing apparatus and method based on deep learning and neural network learning, 11,341,375(US), 2022

◾ Apparatus and method to train autonomous driving model, and autonomous driving apparatus, 10,791,979(US), 2020

◾ Tomography apparatus and method for reconstructing tomography image thereof, 10,339,675(US), 2019

◾ Apparatus and method for object recognition and for training object recognition model, 10,133,938(US), 2018

◾ AI 클러스터 혁신생태계 확산 (참여대학 연구책임자), 2025-2030, 서울RISE사업, 서울연구원

◾ 순환적 생성형 인공지능과 자기지도 학습 모델 개발을 통한 저선량 복부CT영상으로부터의 연부조직 예측 (연구책임자), 2025-2028, 개인기초연구사업(우수신진연구), 한국연구재단

◾ 인간지향 체어사이드 K덴탈 솔루션개발 (연구책임자), 2020-2024, 시장친화형 글로벌 경쟁력확보 제품개발사업, 범부처의료기기연구개발사업단

◾ AI기반 생체정보 분석기술 개발 (연구책임자), 2020-2022, 미래원천기술개발사업, 한국과학기술연구원