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20192025
most citedAdaptive-CS-Net: FastMRI with Adaptive Intelligence

17 citations · 32 across the 11 of their papers we have counts for

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8 papers · 1 filter

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.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★ 8 cited

A Cross-Stitch Architecture for Joint Registration and Segmentation in Adaptive Radiotherapy

Laurens Beljaards, Mohamed S. Elmahdy, Fons Verbeek +1

Recently, joint registration and segmentation has been formulated in a deep learning setting, by the definition of joint loss functions. In this work, we investigate joining these…

eess.IV2020★ 4 cited

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.IV2020

Patient-Specific Finetuning of Deep Learning Models for Adaptive Radiotherapy in Prostate CT

Mohamed S. Elmahdy, Tanuj Ahuja, U. A. van der Heide +1

Contouring of the target volume and Organs-At-Risk (OARs) is a crucial step in radiotherapy treatment planning. In an adaptive radiotherapy setting, updated contours need to be gen…

eess.IV2019★ 17 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…

eess.IV2019

Adversarial optimization for joint registration and segmentation in prostate CT radiotherapy

Mohamed S. Elmahdy, Jelmer M. Wolterink, Hessam Sokooti +2

Joint image registration and segmentation has long been an active area of research in medical imaging. Here, we reformulate this problem in a deep learning setting using adversaria…