15.4k citations · 16.2k across the 13 of their papers we have counts for
13 papers
PVP: Personalized Video Prior for Editable Dynamic Portraits using StyleGAN
Kai-En Lin, Alex Trevithick, Keli Cheng +5
Portrait synthesis creates realistic digital avatars which enable users to interact with others in a compelling way. Recent advances in StyleGAN and its extensions have shown promi…
Multi-Task Edge Prediction in Temporally-Dynamic Video Graphs
Osman Ülger, Julian Wiederer, Mohsen Ghafoorian +2
Graph neural networks have shown to learn effective node representations, enabling node-, link-, and graph-level inference. Conventional graph networks assume static relations betw…
Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic Segmentation
Erik Stammes, Tom F. H. Runia, Michael Hofmann +1
Semantic segmentation is a task that traditionally requires a large dataset of pixel-level ground truth labels, which is time-consuming and expensive to obtain. Recent advancements…
3D Convolutional Neural Networks Image Registration Based on Efficient Supervised Learning from Artificial Deformations
Hessam Sokooti, Bob de Vos, Floris Berendsen +5
We propose a supervised nonrigid image registration method, trained using artificial displacement vector fields (DVF), for which we propose and compare three network architectures.…
I Bet You Are Wrong: Gambling Adversarial Networks for Structured Semantic Segmentation
Laurens Samson, Nanne van Noord, Olaf Booij +3
Adversarial training has been recently employed for realizing structured semantic segmentation, in which the aim is to preserve higher-level scene structural consistencies in dense…
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Hugo J. Kuijf, J. Matthijs Biesbroek, Jeroen de Bresser +41
Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are o…
Comparison of U-net-based Convolutional Neural Networks for Liver Segmentation in CT
Hans Meine, Grzegorz Chlebus, Mohsen Ghafoorian +2
Various approaches for liver segmentation in CT have been proposed: Besides statistical shape models, which played a major role in this research area, novel approaches on the basis…
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection
Mohsen Ghafoorian, Cedric Nugteren, Nóra Baka +2
Convolutional neural networks have been successfully applied to semantic segmentation problems. However, there are many problems that are inherently not pixel-wise classification p…
Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR
Mohsen Ghafoorian, Jonas Teuwen, Rashindra Manniesing +4
Ventricular volume and its progression are known to be linked to several brain diseases such as dementia and schizophrenia. Therefore accurate measurement of ventricle volume is vi…
Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation
Mohsen Ghafoorian, Alireza Mehrtash, Tina Kapur +11
Magnetic Resonance Imaging (MRI) is widely used in routine clinical diagnosis and treatment. However, variations in MRI acquisition protocols result in different appearances of nor…
A Survey on Deep Learning in Medical Image Analysis
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi +6
Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning…
Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin
Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes +8
Lacunes of presumed vascular origin (lacunes) are associated with an increased risk of stroke, gait impairment, and dementia and are a primary imaging feature of the small vessel d…
Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities
Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes +7
The anatomical location of imaging features is of crucial importance for accurate diagnosis in many medical tasks. Convolutional neural networks (CNN) have had huge successes in co…