Dr. Aamir Raja is a Medical Physicist. He joined Khalifa University in August 2020 as an Assistant Professor where he co-founded the Medical Physics wing in the physics department and co-developed an accredited M.Sc program in medical physics.
Prior to his appointment, Dr Raja was the Senior Research Fellow in the Department of Academic Radiology at the University of Otago, Christchurch, New Zealand. He also held a Visiting Research Fellowship at the University of Canterbury, NZ and a Visiting Academic Teaching Staff position at the ARA Institute of Canterbury, NZ. Dr Raja also held a secondment position in the industry. He is a Life Member and Fellow of the Union for International Cancer Control. Currently, he also holds Honorary Senior Research Fellowship with the University of Otago Christchurch.
Dr. Raja has been working in x-rays imaging since 2009, beginning with the completion of his PhD in Medical Physics from Canterbury University. His research interest includes but is not limited to radiation physics and medical imaging physics, particularly x-ray imaging with small pixel detectors for medical and diagnostic imaging applications. Moreover, Dr. Raja and his colleagues contributed to the development of the world’s first commercial preclinical and clinical spectral photon-counting computed tomography, producing color x-ray images with applications to biology and medicine such as characterizing bone health, cartilage health, and metal implants imaging, cancer imaging with targeted nanoparticles, atherosclerosis (measuring calcification, lipid content), and arthritis (crystal arthropathies).
Dr. Raja has supervised more than twenty full-time thesis students. Out of twenty, he has directly supervised twelve University of Otago NZ students, two Master-level students from the University of Canterbury NZ and two from the National University of Science and Technology Pakistan (ongoing), and several visiting international PhD students, summer students, senior-level projects (4th year UG students) and interns.
Overall, Dr. Raja’s research has contributed to >25 journal publications, >20 peer-reviewed conference proceedings, >42 published abstracts, and two book chapters. He was PI/NI on various NZ-funded projects worth over $500K to work on cardiovascular disease imaging, joint diseases, and cancer imaging using photon-counting CT. He has also been awarded Khalifa University Faculty Startup Grant worth ~$300K in 2021.
Initiating machine learning-based CT radiation monitoring database in the emirates of Abu Dhabi
In UAE, there is no formal system or software available at the national level to automatically collect computed tomography radiation monitoring data into a central database and allow hospitals to compare their CT doses. This project aims to develop a machine learning-based smart radiation monitoring tool that connects with computed tomography scanners and/or hospital PACS (Picture archiving and communication system) servers and collects all data automatically into a central database.
Imaging assessment of multiple high-atomic number nanoparticle contrast elements for multi-energy CT
This project aims to combine nanoparticle technology with low-dose multi-energy (spectral) computed tomography (CT) systems and apply task-based image quality assessment to identify non-toxic high-atomic number (Z) elements that produce maximum CT contrast. For this project, task-based image quality characterization will be performed using a clinically established dual-energy CT scanner and a laboratory version of an emerging photon-counting CT scanner. Commercially viable non-toxic multiple high-Z nanoparticle-based contrast elements will be assessed simultaneously.
Development of machine learning based artefacts reduction software using multi-energy CT
In CT imaging, when x-rays pass through high-density structures such as calcified regions and metallic implants, many physical effects such as beam hardening, photon starvation and partial volume effects cause metal-related artefacts. Metal artefacts are considered one of the major clinical challenges as it significantly deteriorates the signal-to-noise ratio. These artefacts limit the accurate assessment of image quality in metal and adjacent non-metal regions which severely impairs the assessment of complications of metal implants and the tissues in the vicinity of implants. This project will exploit the access to the photon-counting CT scanner and develop machine learning-based image denoising/correction techniques for clinical applications.
Development of AI-based material reconstruction software using multi-energy CT
Multi-energy photon-counting CT is an emerging imaging method that provides multiple energy bins in a single CT acquisition. Material decomposition in photon-counting CT is a technique that utilizes the energy dependence of the linear attenuation coefficient to identify and quantify multiple materials in a sample that are indistinguishable from one another in conventional CT. This project aims to develop artificial intelligence (machine learning/deep learning/convolution neural networks) based post-image reconstruction material decomposition algorithm using a small animal research photon counting x-ray CT system.
List of Current Khalifa University Thesis Students
Student Name: Osama Sikandar Khan (KU PhD)
Thesis title: Development of High-Resolution Bench-Top Photon Counting X-Ray System for 2-D and 3-D Imaging Start Date: Spring 2025
Supervisory Team: Dr. Aamir Raja, Assoc Prof Nabil Maalej, Assoc Prof Mohamed Jouini
Student Name: Mohammad Alzaabi (KU PhD)
Thesis title: Tissue Characterization with a Benchtop X-ray Imaging System Start Date: Fall 2024
Supervisory Team: Assoc Prof Nabil Maalej and Dr. Aamir Raja,
Student Name: Hermon Bereket Teklesenbet (KU PhD)
PhD Thesis Title: Explainable Artificial Intelligence (XaI) for Medical Image Analysis and Diagnosis Start Date: Spring 2024
Supervisory Team: Assoc Prof Zeyar Aung and Dr. Aamir Raja,
Student Name: Heba Mustafa (KU PhD)
Phd Thesis title: Development of New Parametric Colour X-Ray Imaging Start Date: Fall 2022
Supervisory Team: Assoc Prof Nabil Maalej, Dr. Aamir Raja, Prof Mohamed Lamine Seghier
Student Name: Briya Tariq (KU PhD)
Thesis title: Development of Machine Learning Based Artefacts Reduction Software Using Multienergy CT Start Date: Fall 2021
Supervisory Team: Dr. Aamir Raja, Assoc Prof Zeyar Aung
Student Name: Yusuf Olatunji Ibrahim (KU PhD)
Thesis title: Novel Nanoparticles for Targeting and Imaging of Cancer Cells. Start Date: Fall 2021
Supervisory Team: Assoc Prof Nabil Maalej, Dr. Aamir Raja, Assoc Prof Ahsan Qurashi
List of Past Khalifa University Thesis Students
1. Kyriaki Katsikari., (2024), , Master of Science in Medical Physics. Khalifa University, Abu Dhabi, UAE
2. Manar Issam Katib., (2024), , Master of Science in Medical Physics. Khalifa University, Abu Dhabi, UAE
3. Noora Ali Rahmani., (2024), , Master of Science in Medical Physics. Khalifa University, Abu Dhabi, UAE
4. Ahmed Alhamedi., (2024), , Master of Science in Medical Physics. Khalifa University, Abu Dhabi, UAE
List of Past Thesis-level students:
1. Krishna Mani Chapagain., (2023), , PhD Thesis. Department of Orthopaedic Surgery and Musculoskeletal Medicine. University of Otago, Christchurch, New Zealand
2. Kenzie Baer., (2021), , PhD Thesis. Department of Orthopaedic Surgery and Musculoskeletal Medicine. University of Otago, Christchurch, New Zealand
3. Shishir Dahal., (2021), , PhD Thesis. Department of Radiology. University of Otago, Christchurch, New Zealand
4. Aysouda Matanaghi., (2021), , PhD Thesis. Department of Radiology. University of Otago, Christchurch, New Zealand
5. Fatima Asghariomabad., (2020), , PhD Thesis. Department of Radiology. University of Otago, Christchurch, New Zealand
6. Chiara Lowe., (2020), , PhD Thesis. Department of Radiology. University of Otago, Christchurch, New Zealand
7. Maya Rajeswari Amma., (2020), , PhD thesis. Department of Radiology. University of Otago, Christchurch, New Zealand.
8. Emmanuel Marfo., (2019), , PhD Thesis. Department of Radiology. University of Otago, Christchurch, New Zealand
9. Mahdieh Moghiseh., (2018), , PhD Thesis. Department of Radiology. University of Otago, Christchurch, New Zealand
10. Tara Dalefield., (2018), , Master of Science in Medical Physics. University of Canterbury, New Zealand
11. Emily Searle., (2018), , Master of Science in Medical Physics. Quantitative imaging of vulnerable atherosclerotic plaque using MARS Spectral CT, Master of Science in Medical Physics. University of Canterbury, New Zealand
PhD studentships are available.
