I’m a Senior Image Processing and Data Scientist, currently collaborating with physicists, clinicians, and industry partners on cardiovascular magnetic resonance imaging (CMR) research. My work bridges data analysis, image processing, and deep learning, with a focus on advancing in vivo imaging and creating compelling visual representations of complex data.

Outside of work, I’m a proud dad and an enthusiastic amateur photographer 📷. Currently based in the UK.

• 🎓 Physicist with a PhD in Image Processing and a strong academic background.

• 🧪 Passionate about research, data analysis and visualisation, and solving complex problems with computational methods.

• 💻 Python programmer with a keen interest in image processing and AI.

• 📚 Lifelong learner, always exploring new technologies.

• 📸 Strong interest in photography in my free time.

• 🫀 I’m currently working on software tools for Cardiac Diffusion Tensor Imaging

• Programming Languages: Python, MATLAB, Latex
• Frameworks & Libraries: Numpy, Pandas, SciPy, scikit-image, TensorFlow, ITK-elastix, OpenCV, ImageMagick, DiPy, Fury
• Tools & Platforms: macOS, Ubuntu, Visual Studio Code, Pycharm, Docker, Paraview, GitHub

• ⭐️ INDI - Post-processing toolbox for cardiac in-vivo diffusion tensor imaging.
• ⭐️ Voxel DICOM viewer app - Cross platform DICOM viewer with useful diffusion information overlays.
• cDTI DICOM to NIFTI - Tool for converting cDTI DICOMs to NIFTI files with anonimysation options.
• STEAM U-Net segmentation - Automatic segmentation and classification of cardiovascular images with convolutional neural networks removing the need for an expert clinician to manually catalog and segment diffusion images. Publication link (Python, TensorFlow).

• In vivo diffusion tensor prediction with convolutional neural networks: promising approach to minimise the amount of data required in clinical DT-CMR studies. Publications link 1 and link 2 (Python, TensorFlow, Pytorch).
• Automatic batch-processing of large histology images, including image registration and extracting the main direction of muscle cells. (MATLAB + Python).
• In-line post-processing in real-time using the Open Recon platform, providing the operator with DT-CMR results and feedback on scan success/failure during scan acquisition, leading to improved quality and efficiency. (Python, TensorFlow).

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• 🌐 Imperial College personal page
• ✉️ Email: p.f.ferreira05@imperial.ac.uk
• 📚 Google Scholar / ORCID

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⚡ Fun fact

“O pensamento científico é um ato de liberdade.” (“Scientific thinking is an act of freedom.”)

Ruy Luís Gomes - Portuguese mathematician

I’m always open to new opportunities and collaborations, so feel free to reach out if you’d like to connect or discuss potential projects.

Citations 2832 / h-index 25 / i10-index 37 (data from Google Scholar)

• Ferreira, P.F., et al. (2022), Accelerating Cardiac Diffusion Tensor Imaging With a U-Net Based Model: Toward Single Breath-Hold. J Magn Reson Imaging, 56: 1691-1704. link

• Ferreira PF, et al. Automating in vivo cardiac diffusion tensor postprocessing with deep learning–based segmentation. Magn Reson Med. 2020; 84: 2801–2814. link

• Tänzer, M. et al. (2022). Faster Diffusion Cardiac MRI with Deep Learning-Based Breath Hold Reduction. In: Medical Image Understanding and Analysis. MIUA 2022. Lecture Notes in Computer Science, vol 13413. Springer, Cham. link

• Wang, F. et al. (2024). Groupwise Deformable Registration of Diffusion Tensor Cardiovascular Magnetic Resonance: Disentangling Diffusion Contrast, Respiratory and Cardiac Motions. In: Linguraru, M.G., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. MICCAI 2024. Lecture Notes in Computer Science, vol 15002. Springer, Cham. link

• Jo Schlemper, Guang Yang, Pedro Ferreira, et al. Stochastic deep compressive sensing for the reconstruction of diffusion tensor cardiac MRI. CoRR, abs/1805.12064, 2018. [Impact Factor: 9.73] link

• Ramyah Rajakulasingam, Pedro F Ferreira, et al. Characterization of dynamic changes in cardiac microstructure after reperfused ST-elevation myocardial infarction by biphasic diffusion tensor cardiovascular magnetic resonance, European Heart Journal, Volume 46, Issue 5, 1 February 2025, Pages 454–469, link.

• Nielles-Vallespin S, Khalique Z, Ferreira PF, et al. Assessment of Myocardial Microstructural Dynamics by In Vivo Diffusion Tensor Cardiac Magnetic Resonance. J Am Coll Cardiol. 2017; 69: 661-676. link

• Khalique Z, Ferreira PF, et al. Diffusion Tensor Cardiovascular Magnetic Resonance Imaging: A Clinical Perspective. JACC Cardiovasc Imaging. 2020; 13: 1235-1255. link

• Nielles-Vallespin S, Scott A, Ferreira P, et al. Cardiac Diffusion: Technique and Practical Applications. J Magn Reson Imaging. 2020; 52: 348-368. link

• Ferreira PF, Gatehouse PD, Mohiaddin RH, Firmin DN. Cardiovascular magnetic resonance artefacts. J Cardiovasc Magn Reson. 2013; 15: 41. link

• Gerber BL, et al. Myocardial first-pass perfusion cardiovascular magnetic resonance: history, theory, and current state of the art. J Cardiovasc Magn Reson. 2008; 10: 18. link

Imaging Artifacts Chapter: Pedro F Ferreira, et al. Title: Basic Principles of Cardiovascular Magnetic Resonance Imaging: Physics and Imaging Techniques. Editors: Mushabbar A. Syed, Subha Raman, Orlando P. Simonetti. Springer 2015. link

2025 Chair of the Cardiac Diffusion Special Interest Group (Society for Cardiovascular Magnetic Resonance, SCMR).

I am currently one of the lecturers in a biannual cardiovascular magnetic resonance (CMR) course at the Royal Brompton Hospital. Talks include: Physics in myocardial perfusion imaging, CMR imaging artefacts, and CMR at 3T.

2022-2023 Member of the ISMRM (International Society of Magnetic Resonance in Medicine) Education Committee.

Student supervision:

• Co-supervision of Physics & Clinical PhD students (Imperial College, London)
• Supervision of MSc students (Imperial College, London).
• Supervision of UROP (Undergraduate Research Opportunities Programme) students.