Byeongjoon Kim - researchr alias

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Viewing Publication 1 - 7 from 7

2023

Helical Artifact Reduction Method Using Image Segmentation With CNN Denoising TechniqueSeungwon Choi, Byeongjoon Kim, Chulkyu Park, Jueon Park, YouSuk Kim, Sungil Choi, Jongduk Baek. access, 11:49261-49272, 2023. [doi]

2022

A Methodology to Train a Convolutional Neural Network-Based Low-Dose CT Denoiser With an Accurate Image Domain Noise Insertion TechniqueByeongjoon Kim, Sarah E. Divel, Norbert J. Pelc, Jongduk Baek. access, 10:86395-86407, 2022. [doi]

2021

GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy ImagesSungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon. iclr 2021: [doi]

Weakly-supervised progressive denoising with unpaired CT imagesByeongjoon Kim, Hyunjung Shim, Jongduk Baek. mia, 71:102065, 2021. [doi]

2020

A performance comparison of convolutional neural network based anthropomorphic model observer and linear model observer for signal-known statistically detection tasksMinah Han, Byeongjoon Kim, Jongduk Baek. miipop 2020: 1131612 [doi]

A Convolutional Neural Network-Based Anthropomorphic Model Observer for Signal Detection in Breast CT Images Without Human-Labeled DataByeongjoon Kim, Minah Han, Jongduk Baek. access, 8:162122-162131, 2020. [doi]

Convolutional neural network-based anthropomorphic model observer for breast cone-beam CT imagesByeongjoon Kim, Minah Han, Jongduk Baek. miipop 2020: [doi]

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