Wojtek Zbijewski is an Assistant Professor at JHU Biomedical Engineering with over 15 years of experience in medical imaging research, ranging from model-based CT reconstruction to cone-beam CT system optimization to shape and texture analysis.
Alejandro Lopez Montes, PhD, is a postdoctoral fellow at Johns Hopkins BME. His research focuses of accurate models of imaging physics to support development of new x-ray CT systems for applications ranging from neurology to orthopedics. He received his PhD in Physics at Complutense University of Madrid.
Selam Waktola is a postdoctoral research fellow in the Department of Biomedical Engineering at Johns Hopkins, currently working on AI for medical image analysis in image-guided brain surgery and CT-based bone radiomics. His past research work includes building different kinds of machine learning and deep learning models for predicting cancer treatments outcomes based on CT, MRI, and endoscopy imaging at the Netherlands Cancer Institute, Amsterdam.
Niral Sheth is working with advanced x-ray detectors. His research includes the characterization of 2D/3D imaging performance of CMOS based flat panel detectors for specific CBCT applications.
Stephen Liu is a PhD student in Biomedical Engineering at Johns Hopkins working on dual-energy cone-beam CT, including model-based decomposition algorithms and performance optimization. His previous experience at UC Davis includes scintillator design, DSP, and simulations for the whole-body PET scanner.
Gengxin Xi is a PhD student in Biomedical Engineering working on performance assessment of ultra-high resolution CT systems in imaging of bone microarchitecture and on image analytics for bone radiomics.
Yang is a graduate student currently working on his Master’s thesis with Dr. Zbijewski investigating the distribution of scatter in various energy channels for a CdZnTe Photon-Counting Detector and its effects on medical image quality.
Danny Poinapen developed a advanced morphological analysis methods for quantification of human pancreatic tumors visualized using 3D clearing microscopy. His goal was to link quantitative features of tumor shape to its invasiveness and patient outcomes.
Chumin Zhao worked on 2D/3D imaging using versatile twin robotic x-ray imaging system. His research included development of a system simulation framework and optimization of imaging orbits for variety of quantitative applications.
Yuan Zhou was an MSE student in Biomedical Engineering. She developed AI approaches for quantitative analysis of 3D imaging data, including cell detection in clearing microscopy and trabecular segmentation in ultra-high resolution CT.