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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Bédard, S., Karthik, E. N., Tsagkas, C., Pravatà, E., Granziera, C., Smith, A. C., Weber, K. A., & Cohen-Adad, J. (2025). Towards contrast-agnostic soft segmentation of the spinal cord. Medical Image Analysis, 101, 103473-103473. External link
Karthik, E. N., Valošek, J., Farner, L., Pfyffer, D., Schading, S., Lebret, A., Dávid, G., Smith, A. C., Weber, K. A., Seif, M., Freund, P., & Cohen-Adad, J. (2024, October). SCIsegV2: A Universal Tool for Segmentation of Intramedullary Lesions in Spinal Cord Injury [Paper]. 3rd International Workshop on Applications of Medical Artificial Intelligence (AMAI 2024/MICCAI 2024), Marrakesh, Morocco. Published in Lecture notes in computer science. External link
Karthik, E. N., Valošek, J., Smith, A. C., Pfyffer, D., Schading, S., Farner, L., Weber, K. A., Freund, P., & Cohen-Adad, J. (2024). SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans. Radiology Artificial Intelligence. External link
Karthik, E. N., Cheriet, F., & Laporte, C. (2023). Uncertainty Estimation in Unsupervised MR-CT Synthesis of Scoliotic Spines. IEEE Open Journal of Engineering in Medicine and Biology, 7 pages. External link
Lemay, A., Gros, C., Karthik, E. N., & Cohen-Adad, J. (2023). Label fusion and training methods for reliable representation of inter-rater uncertainty. The Journal of Machine Learning for Biomedical Imaging, 1(January 20), 1-27. External link
McGinnis, J., Karthik, E. N., Rühling, S., Wurm, R., Stern, K., Bédard, S., Wiltgen, T., Berthele, A., Zimmer, C., Hemmer, B., Benedikt, W., Rückert, D., Kirschke, J., Cohen-Adad, J., & Mühlau, M. (2023, October). Towards generalizable spinal cord lesion segmentation in multiple sclerosis [Poster]. 9th Joint ECTRIMS-ACTRIMS meeting (MSMilan 2023), Milan, Italy (1 page). Published in Multiple Sclerosis Journal, 29(3S). External link
Valošek, J., Karthik, E. N., Bouthillier, M., Schading, S., Farner, L., Pfyffer, D., Smith, A. C., Weber, K. A., Freund, P., & Cohen-Adad, J. (2024, May). Automatic segmentation of T2-weighted hyperintense lesions in spinal cord injury [Abstract]. ISMRM & ISMRT annual Meeting & Exhibition, Singapore, Singapore. Published in Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition. External link
