Image Synthesis

• 

  Image reconstruction by domain-transform manifold learning

  • Published on: March, 2017
  • Bruce R. Rosen, Jeremiah Z. Liu, Matthew S. Rosen, Bo Zhu
  • Code Available

  Magnetic resonance imaging (MRI), X-ray computed tomography (CT), positron emission tomography (PET), ultrasound, and radio astronomy all rely on imag ...

• 

  Deep CT to MR Synthesis Using Paired and Unpaired Data

  • Published on: May, 2019
  • Wonmo Jung, In Ho Han, Hakil Kim, Xuenan Cui, Cheng-Bin Jin, Jae Il Lee, Seongsu Joo, Mingjie Liu, Eunsik Park...
  • Code Available

  Magnetic resonance (MR) imaging plays a highly important role in radiotherapy treatment planning for the segmentation of tumor volumes and organs. How ...

• 

  Retina Blood Vessel Segmentation

  • Published on: June, 2018
  • Orobix
  • Code Available

  Retina blood vessel segmentation with a convolution neural network (U-net) takes up the binary classification task to predicts if each pixel in the fu ...

• 

  Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network

  • Published on: March, 2018
  • Eunhee Kang, Won Chang, and Jong Chul Ye, Jaejun Yoo
  • Code Available

  X-RAY computed tomography (CT) is one of the most valuable imaging techniques in clinics. However, X-ray CT causes potential cancer risks due to radia ...

• 

  Synthesizing Filamentary Structured Images with GANs

  • Published on: June, 2017
  • Huiqi Li, Li Cheng, He Zhao
  • Code Available

  In this model a novel data-driven approach is used to synthesize filamentary structured images like retinal fundus images and neuronal images when gro ...

• 

  Deep Adversarial Data Augmentation for Extremely Low Data Regime Classification

  • Published on: August, 2018
  • Zhangyang Wang, Dong Liu, Qing Ling, Xiaofeng Zhang
  • Code Available

  Deep learning has revolutionized the performance of classification, but in many settings where either massively annotating labels is a labor-intensive ...

• 

  Medical Image Synthesis with Deep Convolutional Adversarial Networks

  • Published on: December, 2018
  • Dinggang Shen, Dong Nie, Su Ruan, Li Wang, Qian Wang, Jun Lian, Caroline Petitjean, Roger Trullo
  • Code Available

  The approach proposes a deep convolutional adversarial network framework by adversarially training FCN as the generator and CNN as the discriminator t ...

• 

  Attaining Real Time Super Resolution for Microscopic Images Using GAN

  • Published on: October, 2020
  • Yatender Kumar, Vibhu Bhatia
  • Code Available

  Aiming to improve existing deep-learning based method to perform Super-Resolution Microscopy, model uses a tiling strategy, which takes advantage of p ...

• 

  PWLS-ULTRA: An Efficient Clustering and Learning-Based Approach for Low-Dose 3D CT Image Reconstruction

  • Published on: June, 2018
  •  Jeffrey A. Fessler,  Yong Long, Xuehang Zheng,  Saiprasad Ravishankar
  • Code Available

  CT image reconstruction methods decrease exposure to radiations while ensuring ensure high image quality in low dose CT. This model presents a new pen ...

• 

  DC2Anet: Generating Lumbar Spine MR Images from CT Scan Data Based on Semi-Supervised Learning

  • Published on: December, 2018
  • Jung Hwan Lee, In Ho Han, Hakil Kim, Xuenan Cui, Cheng-Bin Jin, Jae Il Lee, Seongsu Joo, Mingjie Liu, Eunsik P...
  • Code Available

  Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are widely used in many clinical applications. MRI plays an important role in diagnosis ...