56 citations · 73 across the 5 of their papers we have counts for
5 papers
A two-stage approach for beam hardening artifact reduction in low-dose dental CBCT
T. Bayaraa, C. M. Hyun, T. J. Jang +2
This paper presents a two-stage method for beam hardening artifact correction of dental cone beam computerized tomography (CBCT). The proposed artifact reduction method is designed…
Deep Learning-Based Solvability of Underdetermined Inverse Problems in Medical Imaging
Chang Min Hyun, Seong Hyeon Baek, Mingyu Lee +2
Recently, with the significant developments in deep learning techniques, solving underdetermined inverse problems has become one of the major concerns in the medical imaging domain…
Improving learnability of neural networks: adding supplementary axes to disentangle data representation
Bukweon Kim, Sung Min Lee, Jin Keun Seo
Over-parameterized deep neural networks have proven to be able to learn an arbitrary dataset with 100 training accuracy. Because of a risk of overfitting and computational cost…
Automatic evaluation of fetal head biometry from ultrasound images using machine learning
Hwa Pyung Kim, Sung Min Lee, Ja-Young Kwon +3
Ultrasound-based fetal biometric measurements, such as head circumference (HC) and biparietal diameter (BPD), are commonly used to evaluate the gestational age and diagnose fetal c…
Machine-learning-based nonlinear decomposition of CT images for metal artifact reduction
Hyung Suk Park, Sung Min Lee, Hwa Pyung Kim +1
Computed tomography (CT) images containing metallic objects commonly show severe streaking and shadow artifacts. Metal artifacts are caused by nonlinear beam-hardening effects comb…