Mohamed A. Naser

According to our database, Mohamed A. Naser authored at least 11 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

DASS Good: Explainable Data Mining of Spatial Cohort Data.

Andrew Wentzel, Carla Floricel, Guadalupe Canahuate, Mohamed A. Naser, Abdallah S. Mohamed, Clifton D. Fuller, Lisanne van Dijk, G. Elisabeta Marai

Comput. Graph. Forum, June, 2023

Improving Prediction of Late Symptoms using LSTM and Patient-reported Outcomes for Head and Neck Cancer Patients.

Yaohua Wang, Lisanne van Dijk, Abdallah Sherif Radwan Mohamed, Mohamed A. Naser, Clifton David Fuller, Xinhua Zhang, G. Elisabeta Marai, Guadalupe Canahuate

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

Why is the Winner the Best?

Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha M. Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias P. Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, A. Emre Kavur, Oldrich Kodym, Michal Kozubek, Jianning Li, Hongwei Bran Li, Jun Ma, Carlos Martín-Isla, Bjoern H. Menze, J. Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, Jonathan Rafael-Patino, Vivek Singh Bawa, Stefanie Speidel, Carole H. Sudre, Kimberlin M. H. van Wijnen, Martin Wagner, D. Wei, Amine Yamlahi, Moi Hoon Yap, C. Yuan, Maximilian Zenk, A. Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, J. Cho, C. Choi, Q. Dou, Ivan Ezhov, Christoph M. Friedrich, C. Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García-Faura, Maria Grammatikopoulou, S. Hong, Mostafa Jahanifar, I. Jang, Abdolrahim Kadkhodamohammadi, I. Kang, Florian Kofler, S. Kondo, Hugo Jaco Kuijf, M. Li, M. Luu, Tomaz Martincic, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, S. Pang, J. Park, S. Park, Szymon Plotka, Élodie Puybareau, Nasir M. Rajpoot, K. Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Stepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Hélène Urien, João L. Vilaça, Kareem A. Wahid, H. Wang, J. Wang, L. Wang, X. Wang, Benedikt Wiestler, Marek Wodzinski, F. Xia, J. Xie, Z. Xiong, S. Yang, Y. Yang, Z. Zhao, Klaus H. Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Head and neck tumor segmentation in PET/CT: The HECKTOR challenge.

Valentin Oreiller, Vincent Andrearczyk, Mario Jreige, Sarah Boughdad, Hesham Elhalawani, Joël Castelli, Martin Vallières, Simeng Zhu, Juanying Xie, Ying Peng, Andrei Iantsen, Mathieu Hatt, Yading Yuan, Jun Ma, Xiaoping Yang, Chinmay Rao, Suraj Pai, Kanchan Ghimire, Xue Feng, Mohamed A. Naser, Clifton D. Fuller, Fereshteh Yousefirizi, Arman Rahmim, Huai Chen, Lisheng Wang, John O. Prior, Adrien Depeursinge

Medical Image Anal., 2022

Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT.

Vincent Andrearczyk, Valentin Oreiller, Moamen Abobakr, Azadeh Akhavanallaf, Panagiotis Balermpas, Sarah Boughdad, Leo Capriotti, Joël Castelli, Catherine Cheze Le Rest, Pierre Decazes, Ricardo Correia, Dina El-Habashy, Hesham Elhalawani, Clifton D. Fuller, Mario Jreige, Yomna Khamis, Agustina La Greca Saint-Esteven, Abdallah Sherif Radwan Mohamed, Mohamed A. Naser, John O. Prior, Su Ruan, Stephanie Tanadini-Lang, Olena Tankyevych, Yazdan Salimi, Martin Vallières, Pierre Vera, Dimitris Visvikis, Kareem A. Wahid, Habib Zaidi, Mathieu Hatt, Adrien Depeursinge

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2022

2021

Combining Tumor Segmentation Masks with PET/CT Images and Clinical Data in a Deep Learning Framework for Improved Prognostic Prediction in Head and Neck Squamous Cell Carcinoma.

Kareem A. Wahid, Renjie He, Cem Dede, Abdallah Sherif Radwan Mohamed, Moamen Abobakr Abdelaal, Lisanne van Dijk, Clifton D. Fuller, Mohamed A. Naser

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021

Progression Free Survival Prediction for Head and Neck Cancer Using Deep Learning Based on Clinical and PET/CT Imaging Data.

Mohamed A. Naser, Kareem A. Wahid, Abdallah Sherif Radwan Mohamed, Moamen Abobakr Abdelaal, Renjie He, Cem Dede, Lisanne van Dijk, Clifton D. Fuller

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021

Head and Neck Cancer Primary Tumor Auto Segmentation Using Model Ensembling of Deep Learning in PET/CT Images.

Mohamed A. Naser, Kareem A. Wahid, Lisanne van Dijk, Renjie He, Moamen Abobakr Abdelaal, Cem Dede, Abdallah Sherif Radwan Mohamed, Clifton D. Fuller

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021

2020

Brain tumor segmentation and grading of lower-grade glioma using deep learning in MRI images.

Mohamed A. Naser, M. Jamal Deen

Comput. Biol. Medicine, 2020

Tumor Segmentation in Patients with Head and Neck Cancers Using Deep Learning Based-on Multi-modality PET/CT Images.

Mohamed A. Naser, Lisanne van Dijk, Renjie He, Kareem A. Wahid, Clifton D. Fuller

Proceedings of the Head and Neck Tumor Segmentation - First Challenge, 2020

2019

Improved Photoacoustic-Based Oxygen Saturation Estimation With SNR-Regularized Local Fluence Correction.

Mohamed A. Naser, Diego R. T. Sampaio, Nina M. Munoz, Cayla A. Wood, Trevor M. Mitcham, Wolfgang Stefan, Konstantin V. Sokolov, Theo Z. Pavan, Rony Avritscher, Richard R. Bouchard

IEEE Trans. Medical Imaging, 2019