40 citations · 82 across the 10 of their papers we have counts for
7 papers · 1 filter
Joint Registration and Segmentation via Multi-Task Learning for Adaptive Radiotherapy of Prostate Cancer
Mohamed S. Elmahdy, Laurens Beljaards, Sahar Yousefi +4
Medical image registration and segmentation are two of the most frequent tasks in medical image analysis. As these tasks are complementary and correlated, it would be beneficial to…
ASL to PET Translation by a Semi-supervised Residual-based Attention-guided Convolutional Neural Network
Sahar Yousefi, Hessam Sokooti, Wouter M. Teeuwisse +4
Positron Emission Tomography (PET) is an imaging method that can assess physiological function rather than structural disturbances by measuring cerebral perfusion or glucose consum…
Esophageal Tumor Segmentation in CT Images using Dilated Dense Attention Unet (DDAUnet)
Sahar Yousefi, Hessam Sokooti, Mohamed S. Elmahdy +5
Manual or automatic delineation of the esophageal tumor in CT images is known to be very challenging. This is due to the low contrast between the tumor and adjacent tissues, the an…
An Adaptive Intelligence Algorithm for Undersampled Knee MRI Reconstruction
Nicola Pezzotti, Sahar Yousefi, Mohamed S. Elmahdy +9
Adaptive intelligence aims at empowering machine learning techniques with the additional use of domain knowledge. In this work, we present the application of adaptive intelligence…
Adaptive-CS-Net: FastMRI with Adaptive Intelligence
Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi +9
Adaptive intelligence aims at empowering machine learning techniques with the extensive use of domain knowledge. In this work, we present the application of adaptive intelligence t…
Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network
Sahar Yousefi, Lydiane Hirschler, Merlijn van der Plas +4
Hadamard time-encoded pseudo-continuous arterial spin labeling (te-pCASL) is a signal-to-noise ratio (SNR)-efficient MRI technique for acquiring dynamic pCASL signals that encodes…
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.…