ABDALLAH ALDAHOUK | Biomedical engineering | Best Researcher Award

Published on by Young Scientists Awards

Mr. ABDALLAH ALDAHOUK l Biomedical engineering
| Best Researcher Award

Istanbul University-Cerrahpaşa | State of Palestine

Mr. ABDALLAH ALDAHOUK , the research conducted focuses on the validation and application of Monte Carlo simulation techniques using GATE (Geant4 Application for Tomographic Emission) software for modeling computed tomography (CT) imaging systems. This work aims to enhance the accuracy and efficiency of CT imaging through advanced computational modeling, allowing precise evaluation of image quality parameters and radiation dose distribution. By employing the Catphan CTP404 phantom, the study investigates the reliability of simulated data in replicating clinical imaging conditions, ensuring that virtual simulations closely mirror real-world CT performance. The research contributes to the optimization of CT imaging protocols, reduction of patient radiation exposure, and improvement of diagnostic accuracy. It further explores the integration of simulation-based calibration and validation methods in biomedical imaging, providing a framework for developing next-generation imaging systems with enhanced resolution and safety. The findings demonstrate the potential of GATE-based Monte Carlo simulations as a powerful tool for medical physicists and biomedical engineers to design, assess, and refine imaging systems without the need for extensive experimental trials. This work represents a significant advancement in computational biomedical engineering, bridging theoretical modeling and clinical imaging applications for improved healthcare diagnostics and imaging innovation.

Profile:  Orcid 

Featured Publication

Aldahouk, A. W., Sezdi, M., & Demir, M. (2026, February). Validation of GATE-based Monte Carlo simulation for clinical CT imaging using the Catphan CTP404 phantom. Radiation Physics and Chemistry, 218, 113364. https://doi.org/10.1016/j.radphyschem.2025.113364

Yunxian Zhang | Biomedical Engineering | Young Scientist Award

Published on by Young Scientists Awards

 Dr. Yunxian Zhang | Biomedical Engineering | Young Scientist Award

 

🌟 Profile Summary

In the realms of medical artificial intelligence, medical image processing, and intelligent planning for robot-assisted surgery, I have cultivated profound expertise through extensive research and practical experience. My commitment to excellence and aptitude for solving complex problems define my scientific endeavors. My focus on machine learning principles and their application in medical diagnostics, coupled with skills in handling intricate medical images, underscores my dedication to advancing healthcare technologies.

 

🌐 Professional Profiles

🌐 Specialties and Skills

Artificial intelligence technology, Medical image processing, Medical imaging, Imagingomics analysis, Medical imaging equipment, Bioinformatics analysis

📅 Selected Recent Conference Presentations

2023 Medical Physics Youth Paper Report Conference, China, Dec. 25, 2023. 2021 Global Digital Economy Conference, China, Aug. 2-3, 2021. IEEE International Conference on Medical Imaging Physics and Engineering, China, Nov. 12-14, 2021. International Symposium on Image Computing and Digital Medicine, China, Dec. 6, 2020.

📚 Educational Background

Ph.D., Biomedical Engineering, Capital Medical University, 2023 Study Area: Surgical robotics, Medical imaging, and medical AI. M.S., Biomedical Engineering, Capital Medical University, 2020 Study Area: Bio-informatics, medical AI. B.S., Biomedical Engineering, Xinxiang Medical University, 2017 Study Area: Biomedical Engineering.

🏢 Working Experience

Lecturer, Medical Imageology Department, Health Science Center, Yangtza University, China Duration: 11/2023 – Present Research Assistant, Bioinstrumentation Department, Capital Medical University, China Duration: 9/2020 – 7/2023 Research Assistant, School of Biomedical Engineering, Capital Medical University, China Duration: 9/2017 – 7/2020.

🔍 Research Projects

Beijing Natural Science Foundation Grant/Award Number: L202005 Key Investigator Beijing Municipal Science and Technology Grant/Award Number: Z211100003521005 Key Investigator Ministry of Science and Technology Grant/Award Number: G20200123023 Key Investigator National Natural Science Foundation of China Grant/Award Number: 61827809 Key Investigator Capital’s Funds for Health Improvement and Research (CFH) Grant/Award Number: 2020-2-2072 Key Investigator

 

 

📚Top Noted Publication

 

 

  • Zhang Y, Zhao J, et al. “Optimal Pedicle Screw Path Planning from Multi-directional Projections.” 2021 IEEE International Conference on Medical Imaging Physics and Engineering.

 

 

 

 

 

 

 

 

Biomedical Engineering