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20112021
most citedAdaptive-CS-Net: FastMRI with Adaptive Intelligence

17 citations · 19 across the 4 of their papers we have counts for

collaborators

9 papers

eess.IV2021

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…

eess.IV20212 cited

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…

eess.IV2020

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…

eess.IV2020

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…

eess.IV201917 cited

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…

eess.IV2019

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…