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Efficient B-mode Ultrasound Image Reconstruction from Sub-sampled RF Data using Deep Learning
Yeo Hun Yoon, Shujaat Khan, Jaeyoung Huh +1
In portable, three dimensional, and ultra-fast ultrasound imaging systems, there is an increasing demand for the reconstruction of high quality images from a limited number of radi…
Deep Learning Diffuse Optical Tomography
Jaejun Yoo, Sohail Sabir, Duchang Heo +10
Diffuse optical tomography (DOT) has been investigated as an alternative imaging modality for breast cancer detection thanks to its excellent contrast to hemoglobin oxidization lev…
Deep Learning for Accelerated Ultrasound Imaging
Yeo Hun Yoon, Jong Chul Ye
In portable, 3-D, or ultra-fast ultrasound (US) imaging systems, there is an increasing demand to reconstruct high quality images from limited number of data. However, the existing…
Framing U-Net via Deep Convolutional Framelets: Application to Sparse-view CT
Yoseob Han, Jong Chul Ye
X-ray computed tomography (CT) using sparse projection views is a recent approach to reduce the radiation dose. However, due to the insufficient projection views, an analytic recon…
Wavelet Domain Residual Network (WavResNet) for Low-Dose X-ray CT Reconstruction
Eunhee Kang, junhong Min, Jong Chul Ye
Model based iterative reconstruction (MBIR) algorithms for low-dose X-ray CT are computationally complex because of the repeated use of the forward and backward projection. Inspire…
Multi-Scale Wavelet Domain Residual Learning for Limited-Angle CT Reconstruction
Jawook Gu, Jong Chul Ye
Limited-angle computed tomography (CT) is often used in clinical applications such as C-arm CT for interventional imaging. However, CT images from limited angles suffers from heavy…