Ramy A. Zeineldin
Orcid: 0000-0002-8630-9046
According to our database1,
Ramy A. Zeineldin
authored at least 14 papers
between 2017 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2024
NeuroIGN: Explainable Multimodal Image-Guided System for Precise Brain Tumor Surgery.
J. Medical Syst., December, 2024
Interactive Surgical Training in Neuroendoscopy: Real-Time Anatomical Feature Localization Using Natural Language Expressions.
IEEE Trans. Biomed. Eng., October, 2024
Dataset, May, 2024
2023
Development of an AI-driven system for neurosurgery with a usability study: a step towards minimal invasive robotics.
Autom., July, 2023
2022
Int. J. Comput. Assist. Radiol. Surg., 2022
Self-supervised iRegNet for the Registration of Longitudinal Brain MRI of Diffuse Glioma Patients.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022
Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022
2021
iRegNet: Non-Rigid Registration of MRI to Interventional US for Brain-Shift Compensation Using Convolutional Neural Networks.
IEEE Access, 2021
A Hybrid Deep Registration of MR Scans to Interventional Ultrasound for Neurosurgical Guidance.
Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021
2020
DeepSeg: deep neural network framework for automatic brain tumor segmentation using magnetic resonance FLAIR images.
Int. J. Comput. Assist. Radiol. Surg., 2020
2018
End-to-End Indoor Navigation Assistance for the Visually Impaired Using Monocular Camera.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018
2017
Navigational path detection for the visually impaired using fully convolutional networks.
Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017