Martin Owusu-Mensah
The researcher has focused on advancing physical science techniques across diverse medical applications, utilizing methodologies such as deep learning, material characterization, and simulation to address challenges in cancer detection, nuclear materials degradation, fusion material synthesis, advanced radiotherapy, joint arthroplasty outcomes, and bone health issues.
Faculty Biography
Dr. Martin Owusu-Mensah is a lecturer at the Department of Physics, KNUST. He is an alumnus of the department graduating in the year 2013 with a BSc in Physics (Biomedical Physics option) and served as a teaching and research assistant at the department. He obtained his Master's degree in Nuclear Engineering from the Université Paris-Saclay, France specializing in Nuclear Power Plant Design. Martin holds a Ph.D. in Nuclear Energy from the Université Paris-Saclay, France specializing in Nuclear Materials and Radiation Safety. Upon completion of his Ph.D., Martin served as a Post-doctoral Research Scholar at North Carolina State University, Raleigh, North Carolina until his appointment as a lecturer at the Department of Physics.Dr. Owusu-Mensah's areas of interest include the development of new materials such as Oxide Dispersion Strengthened (ODS) steels and Silicon Carbide (SiC) which are candidate structural materials for shielding following the Fukushima nuclear accident in 2011. He also has interests in radiation safety and radiation physics to study the health effects of radiation on the public.
Advanced Radiotherapy Techniques
AI in cancer detection
Fusion materials and technologies
Musculoskeletal pain and rehabilitation
Nuclear materials and radiation effects
Total Knee Arthroplasty Outcomes
PS03.10 BIOPHYSICS OF LOW BACK PAIN
Investigating the detection of breast cancer with deep transfer learning using ResNet18 and ResNet34
Open AccessAuthor response for "Investigating the Detection of Breast Cancer with Deep Transfer Learning Using Resnet18 and Resnet34"
Author response for "Investigating the Detection of Breast Cancer with Deep Transfer Learning Using Resnet18 and Resnet34"
Author response for "Investigating the Detection of Breast Cancer with Deep Transfer Learning Using Resnet18 and Resnet34"
Biophysics assessment of proximal fibular osteotomy
Towards clinical use of Varian Clinac iX linear accelerator in a low resource radiotherapy facility: evaluation of commissioning data
Synthesis of Nano-Oxide Precipitates by Implantation of Ti, Y and O Ions in Fe-10%Cr: Towards an Understanding of Precipitation in Oxide Dispersion-Strengthened (ODS) Steels
Open AccessSurprisingly high irradiation-induced defect mobility in Fe3O4 as revealed through in situ transmission electron microscopy
Open AccessIn situ TEM investigation of irradiation-induced amorphization of Fe<sub>3</sub>O<sub>4</sub> and γ -Fe<sub>2</sub>O<sub>3</sub>
Open AccessIn Situ TEM Investigation of Irradiation Induced Amorphization of Fe Oxide
Open AccessIn situ TEM thermal annealing of high purity Fe10wt%Cr alloy thin foils implanted with Ti and O ions
Open AccessDepartment of Physics
Kwame Nkrumah University of Science and Technology