Personal profile
Research interests
- Artificial intelligence and deep learning
- Artificial intelligence applied to medical imaging
- Deep learning for segmentation and classification
- Generative adversarial networks (GANs)
- Self-supervised learning and knowledge transfer
- Advanced medical image processing
- Multimodal medical image synthesis
- Style transfer techniques
- Automatic segmentation of medical images
- Analysis of cardiac and brain images
- AI-assisted diagnosis
- Automatic anomaly detection
- Predictive models for neurodegenerative diseases
- Medical image classification
- Diagnostic assistance systems
- Specialized imaging applications
- AI-based cardiac imaging
- Brain and neurodegenerative imaging
- Computational dermatology
- AI-assisted radiology
Related documents
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being -
SDG 4 Quality Education -
SDG 9 Industry, Innovation, and Infrastructure
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Dive into the research topics where Christian Desrosiers is active. These topics are generated from this person's research output (titles and abstracts), as well as their research interests, awards, and organizations associated with them. Together, they form a unique digital fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Research output
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Imaging coupled filtering: A unified multi-channel framework for multimodal medical image registration and fusion
Liu, H., Zhu, J., Li, H., Desrosiers, C. & Zhang, C., Jun 2026, In: Signal Processing. 243, 110451.Research output: Contribution to journal › Journal Article › peer-review
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MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly Detection
Beizaee, F., Lodygensky, G., Desrosiers, C. & Dolz, J., 2026, Information Processing in Medical Imaging - 29th International Conference, IPMI 2025, Proceedings. Oguz, I., Zhang, S. & Metaxas, D. N. (eds.). Springer Science and Business Media Deutschland GmbH, p. 139-153 15 p. (Lecture Notes in Computer Science; vol. 15830 LNCS).Research output: Contribution to Book/Report types › Contribution to conference proceedings › peer-review
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Prompt Learning With Bounding Box Constraints for Medical Image Segmentation
Gaillochet, M., Noori, M., Dastani, S., Desrosiers, C. & Lombaert, H., 2026, In: IEEE Transactions on Biomedical Engineering. 73, 1, p. 359-368 10 p.Research output: Contribution to journal › Journal Article › peer-review
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Reflect: Rectified Flows for Efficient Brain Anomaly Correction Transport
Beizaee, F., Hajimiri, S., Ben Ayed, I., Lodygensky, G., Desrosiers, C. & Dolz, J., 2026, Medical Image Computing and Computer Assisted Intervention, MICCAI 2025 - 28th International Conference, Proceedings. Gee, J. C., Hong, J., Sudre, C. H., Golland, P., Alexander, D. C., Iglesias, J. E., Venkataraman, A. & Kim, J. H. (eds.). Springer Science and Business Media Deutschland GmbH, p. 456-466 11 p. (Lecture Notes in Computer Science; vol. 15963 LNCS).Research output: Contribution to Book/Report types › Contribution to conference proceedings › peer-review
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Susceptibility DistortionSusceptibility distortion Correction of Diffusion MRIDiffusion MRI with a single Phase-EncodingPhase Encoding Direction
Dargahi, S., Bouix, S. & Desrosiers, C., 2026, Computational Diffusion MRI - 16th International Workshop, CDMRI 2025, Held in Conjunction with MICCAI 2025, Proceedings. Chamberland, M., Chen, Y., Filipiak, P., Hendriks, T., Lv, J., Shailja, S. & Thompson, E. (eds.). Springer Science and Business Media Deutschland GmbH, p. 69-80 12 p. (Lecture Notes in Computer Science; vol. 16205 LNCS).Research output: Contribution to Book/Report types › Contribution to conference proceedings › peer-review