225 citations · 228 across the 4 of their papers we have counts for
4 papers
Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution
Ramy A. Zeineldin, Mohamed E. Karar, Oliver Burgert +1
Automatic segmentation is essential for the brain tumor diagnosis, disease prognosis, and follow-up therapy of patients with gliomas. Still, accurate detection of gliomas and their…
Self-supervised iRegNet for the Registration of Longitudinal Brain MRI of Diffuse Glioma Patients
Ramy A. Zeineldin, Mohamed E. Karar, Franziska Mathis-Ullrich +1
Reliable and accurate registration of patient-specific brain magnetic resonance imaging (MRI) scans containing pathologies is challenging due to tissue appearance changes. This pap…
Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRI
Ramy A. Zeineldin, Mohamed E. Karar, Franziska Mathis-Ullrich +1
Glioblastomas are the most aggressive fast-growing primary brain cancer which originate in the glial cells of the brain. Accurate identification of the malignant brain tumor and it…
DeepSeg: Deep Neural Network Framework for Automatic Brain Tumor Segmentation using Magnetic Resonance FLAIR Images
Ramy A. Zeineldin, Mohamed E. Karar, Jan Coburger +2
Purpose: Gliomas are the most common and aggressive type of brain tumors due to their infiltrative nature and rapid progression. The process of distinguishing tumor boundaries from…