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Minah Han
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2020 – today
- 2022
- [j2]Minah Han
, Hyunjung Shim
, Jongduk Baek
:
Perceptual CT Loss: Implementing CT Image Specific Perceptual Loss for CNN-Based Low-Dose CT Denoiser. IEEE Access 10: 62412-62422 (2022) - [c7]Minwoo Yu, Minah Han, Jongduk Baek:
A convolutional neural network based super resolution technique of CT image utilizing both sinogram domain and image domain data. Medical Imaging: Image Processing 2022 - [c6]Minah Han, Jongduk Baek:
Low-dose CT denoising via CNN trained using images with activation map. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022 - 2020
- [j1]Byeongjoon Kim
, Minah Han, Jongduk Baek
:
A Convolutional Neural Network-Based Anthropomorphic Model Observer for Signal Detection in Breast CT Images Without Human-Labeled Data. IEEE Access 8: 162122-162131 (2020) - [c5]Byeongjoon Kim, Minah Han, Jongduk Baek:
Convolutional neural network-based anthropomorphic model observer for breast cone-beam CT images. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160Y - [c4]Minah Han, Byeongjoon Kim, Jongduk Baek:
A performance comparison of convolutional neural network based anthropomorphic model observer and linear model observer for signal-known statistically detection tasks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131612
2010 – 2019
- 2019
- [c3]Gihun Kim, Minah Han, Hyunjung Shim, Jongduk Baek:
Implementation of an ideal observer model using convolutional neural network for breast CT images. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2019: 109520L - 2018
- [c2]Minah Han, Hanjoo Jang, Jongduk Baek:
Lesion detection performance of cone beam CT images with anatomical background noise: single-slice vs multi-slice human and model observer study. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2018: 105770N - 2016
- [c1]Minah Han, Subok Park, Jongduk Baek:
Effect of anatomical backgrounds on detectability in volumetric cone beam CT images. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2016: 978717
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