[HTML][HTML] A survey on GANs for computer vision: Recent research, analysis and taxonomy
In the last few years, there have been several revolutions in the field of deep learning,
mainly headlined by the large impact of Generative Adversarial Networks (GANs). GANs not …
mainly headlined by the large impact of Generative Adversarial Networks (GANs). GANs not …
Advancements in synthetic CT generation from MRI: A review of techniques, and trends in radiation therapy planning
Background Magnetic resonance imaging (MRI) and Computed tomography (CT) are crucial
imaging techniques in both diagnostic imaging and radiation therapy. MRI provides …
imaging techniques in both diagnostic imaging and radiation therapy. MRI provides …
Conditional GAN with an attention-based generator and a 3D discriminator for 3D medical image generation
Abstract Conditional Generative Adversarial Networks (cGANs) are a set of methods able to
synthesize images that match a given condition. However, existing models designed for …
synthesize images that match a given condition. However, existing models designed for …
Enhanced Leaf Area Index Estimation With CROP-DualGAN Network
Quantitative estimation of regional leaf area index (LAI) is an important basis for large-scale
crop growth monitoring and yield estimation. With the development of deep learning …
crop growth monitoring and yield estimation. With the development of deep learning …
Unpaired synthetic image generation in radiology using gans
D Prokopenko, JV Stadelmann, H Schulz… - Artificial Intelligence in …, 2019 - Springer
In this work, we investigate approaches to generating synthetic Computed Tomography (CT)
images from the real Magnetic Resonance Imaging (MRI) data. Generating the radiological …
images from the real Magnetic Resonance Imaging (MRI) data. Generating the radiological …
[HTML][HTML] Dixon-based thorax synthetic CT generation using generative adversarial network
Abstract Purpose Generation of synthetic Computed Tomography (sCT) images from
Magnetic Resonance (MR) is an imperative, yet not fully resolved task for attenuation …
Magnetic Resonance (MR) is an imperative, yet not fully resolved task for attenuation …
Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution
We went below the MRI acceleration factors (aka, k-space undersampling) reported by all
published papers that reference the original fastMRI challenge 29, and then used deep …
published papers that reference the original fastMRI challenge 29, and then used deep …
Conditional generative adversarial network for predicting 3d medical images affected by alzheimer's diseases
Predicting the evolution of Alzheimer's disease (AD) is important for accurate diagnosis and
the development of personalized treatments. However, learning a predictive model is …
the development of personalized treatments. However, learning a predictive model is …
Tubular shape aware data generation for segmentation in medical imaging
I Sirazitdinov, H Schulz, A Saalbach, S Renisch… - International Journal of …, 2022 - Springer
Purpose Chest X-ray is one of the most widespread examinations of the human body. In
interventional radiology, its use is frequently associated with the need to visualize various …
interventional radiology, its use is frequently associated with the need to visualize various …
Computed tomography image generation from magnetic resonance imaging using Wasserstein metric for MR‐only radiation therapy
J Joseph, C Hemanth… - … Journal of Imaging …, 2022 - Wiley Online Library
Magnetic resonance imaging (MRI) and computed tomography (CT) are the prevalent
imaging techniques used in treatment planning in radiation therapy. Since MR‐only …
imaging techniques used in treatment planning in radiation therapy. Since MR‐only …