About Me

I am a dedicated researcher and data scientist with a PhD in medical technology and a background in biomedical engineering. My work centers on advancing AI-driven healthcare solutions, with a particular focus on medical imaging and diagnostic support systems.
I bring expertise in artificial intelligence, machine learning, and data science, combined with hands-on experience in clinical research, regulatory documentation for medical software, and innovation management. I have led the development and clinical validation of AI systems, secured multi-million NOK research funding, contributed to patent applications, and participated in national and international innovation programs.
Throughout my career, I have collaborated with interdisciplinary teams, industry partners, and end-users to bridge the gap between cutting-edge research and real-world healthcare impact. My passion lies in harnessing data and technology to improve standard of life.
Let us connect to explore opportunities and shape the future of technology innovation.

Contact Details

Mohammed R. S. Sunoqrot
1.306B Fred Kavli-bygget, del 1 Øya
7030 Trondheim, Norway
(+47) 46632587
mohammed.sunoqrot@ntnu.no

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Education

Ph.D. in Medical Technology

NTNU, Norway • August 2021

Thesis title: Computer-Aided Diagnosis of Prostate Cancer Using Multiparametric MRI:
Pre-processing, Segmentation and Quality Control.
Supervisors: Prof. Tone Frost Bathen and Assoc Prof. Mattijs Elschot.

M.Sc. in Biomedical Engineering

University of Dundee, UK • January 2016

Grade: Distinction.
Thesis title: Microultrasound scanning of Oesophogeal tissue.
Supervisors: Prof. Sandy Cochran and Assoc Prof. Ben F. Cox.

B.Sc. in Biomedical Engineering

German-Jordanian University, Jordan • June 2014

Thesis title: Radiation Doses And Risks From Computed Tomography In Jordan.
Supervisor: Assoc Prof. Akeel Alkazwini.

Work

Postdoctoral Researcher

NTNU, Norway • July 2022 - Present

In this multifaceted role, I lead the development and clinical validation of AI-based diagnostic tools for prostate cancer. My work included elevating the technology readiness level (TRL) of the PROVIZ AI system, securing research funding, and designing a prospective clinical study. I prepared regulatory documentation for software as a medical device, mentored master students, and contributed to international collaborations aimed at enhancing AI diagnostics. I have also participated in the REACH incubator and Forge accelerator programs to support innovation and commercialization efforts.

Innovation Project Manager

NTNU, Norway • January 2022 - July 2022

In this dynamic role, I investigated innovative AI solutions for prostate cancer diagnosis. I increased technology readiness levels for a cutting-edge radiology AI product. Additionally, I conducted market analysis, initiated meetings with industry stakeholders and customers, and coordinated seamlessly with the technology transfer office and valued industry partners.

Data & Cloud Manager - Part-time

NTNU, Norway • May 2018 - Present

In this capacity, I am managing and organizing multiple HUNT cloud labs for the CIMORe Group. I skillfully coordinate various aspects of the labs, ensuring compliance, data privacy, technical proficiency, and knowledge dissemination. I am diligently monitoring and addressing any troubleshooting needs that arise during the labs' activities. My responsibilities encompass the collection, management, organization, and secure handling of MR image cohorts. Upholding strict data privacy and security measures is of paramount importance in my role. Moreover, I am closely monitoring image quality and upholding data integrity standards throughout the process.

Skills

  • AI (machine & deep learning)
  • Programming (Python, Matlab)
  • Data Analysis
  • Research
  • Project Management
  • Innovation Management

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Publications

My Publications can be found at cristin and at ORCiD

Selected Publications

  • Artificial intelligence for prostate MRI: open datasets, available applications, and grand challenges.

    European Radiology Experimental.6:35. Mohammed R.S. Sunoqrot, Anindo Saha, Matin Hosseinzadeh, Mattijs Elschot, Henkjan Huisman (2022)

  • A comparison of Generative Adversarial Networks for automated prostate cancer detection on T2-weighted MRI.

    Informatics in Medicine Unlocked 39:101234 Alexandros Patsanis, Mohammed R.S. Sunoqrot, Sverre Langørgen, Hao Wang, Kirsten M. Selnæs, Helena Bertilsson, Tone F. Bathen, Mattijs Elschot (2023)

  • Label-set impact on deep learning-based prostate segmentation on MRI.

    Insights Imaging 14:157 Jakob Meglič, Mohammed R.S. Sunoqrot, Tone F. Bathen, Mattijs Elschot (2023)

  • The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images.

    Diagnostics 11, no. 9: 1690. Mohammed R. S. Sunoqrot, Kirsten M. Selnæs, Elise Sandsmark, Sverre Langørgen, Helena Bertilsson, Tone F. Bathen, and Mattijs Elschot (2021)

  • A Quality Control System for Automated Prostate Segmentation on T2-Weighted MRI.

    Diagnostics 10, no. 9: 714. Mohammed R.S. Sunoqrot, Kirsten M. Selnæs, Elise Sandsmark, Gabriel A. Nketiah, Olmo Zavala-Romero, Radka Stoyanova, Tone F. Bathen, Mattijs Elschot (2020)

  • Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognitions.

    Magn Reson Mater Phy 34, 309–321. Mohammed R.S. Sunoqrot, Gabriel A. Nketiah, Kirsten M. Selnæs, Gabriel A. Nketiah, Tone F. Bathen, Mattijs Elschot(2020)
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Get In Touch.

Feel free to contact me for a potintial colaboration, job offer, or an inquiry.

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