2k citations · 3.3k across the 7 of their papers we have counts for
4 papers · 2 filters
GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification
Maayan Frid-Adar, Idit Diamant, Eyal Klang +3
Deep learning methods, and in particular convolutional neural networks (CNNs), have led to an enormous breakthrough in a wide range of computer vision tasks, primarily by using lar…
Cross-Modality Synthesis from CT to PET using FCN and GAN Networks for Improved Automated Lesion Detection
Avi Ben-Cohen, Eyal Klang, Stephen P. Raskin +5
In this work we present a novel system for generation of virtual PET images using CT scans. We combine a fully convolutional network (FCN) with a conditional generative adversarial…
Synthetic Data Augmentation using GAN for Improved Liver Lesion Classification
Maayan Frid-Adar, Eyal Klang, Michal Amitai +2
In this paper, we present a data augmentation method that generates synthetic medical images using Generative Adversarial Networks (GANs). We propose a training scheme that first u…
Anatomical Data Augmentation For CNN based Pixel-wise Classification
Avi Ben-Cohen, Eyal Klang, Michal Marianne Amitai +2
In this work we propose a method for anatomical data augmentation that is based on using slices of computed tomography (CT) examinations that are adjacent to labeled slices as anot…