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)

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 (HECKTOR@MICCAI, 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)

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 (HECKTOR@MICCAI, 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 (HECKTOR@MICCAI, 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 (HECKTOR@MICCAI, 2021)

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 006; Dina El-Habashy; et al. (HECKTOR@MICCAI, 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; et al. (Medical Image Anal., 2022)

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; et al. (CVPR, 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 (ICHI, 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, 2023)

Overview of the Head and Neck Tumor Segmentation for Magnetic Resonance Guided Applications (HNTS-MRG) 2024 Challenge. - Kareem A. Wahid; Cem Dede; Dina El-Habashy; Serageldin Kamel; Michael K. Rooney; Yomna Khamis; Moamen Abobakr Abdelaal; Sara Ahmed; Kelsey L. Corrigan; Enoch Chang; Stephanie O. Dudzinski; Travis C. Salzillo; et al. (HNTS-MRG@MICCAI, 2024)