Raghavendra Selvan
Tenure Track Assistant Professor
Machine Learning
Universitetsparken 1
2100 København Ø
- 2024
- Published
Operating Critical Machine Learning Models in Resource Constrained Regimes
Selvan, Raghav, Schön, Julian Elisha & Dam, Erik Bjørnager, 2024, Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops: MTSAIL 2023, LEAF 2023, AI4Treat 2023, MMMI 2023, REMIA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8–12, 2023, Proceedings. Springer, p. 325-335 Chapter 29. (Lecture Notes in Computer Science, Vol. 14394).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2023
- Published
Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation
Boserup, Nicklas & Selvan, Raghav, 2023, Proceedings of the Northern Lights Deep Learning Workshop 2023. Septentrio Academic Publishing, 8 p. (Proceedings of the Northern Lights Deep Learning Workshop, Vol. 4).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2022
- Published
Identifying Partial Mouse Brain Microscopy Images from the Allen Reference Atlas Using a Contrastively Learned Semantic Space
Antanavicius, J., Leiras, Roberto & Selvan, Raghav, 2022, Biomedical Image Registration - 10th International Workshop, WBIR 2022, Proceedings. Hering, A., Schnabel, J., Zhang, M., Ferrante, E., Heinrich, M. & Rueckert, D. (eds.). 1 ed. Springer Science and Business Media Deutschland GmbH, p. 166-176 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13386 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Interpreting Latent Spaces of Generative Models for Medical Images using Unsupervised Methods
Schön, Julian Elisha, Selvan, Raghav & Petersen, Jens, 2022, Deep Generative Models: Second MICCAI Workshop, DGM4MICCAI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Springer, p. 24-33 (Lecture Notes in Computer Science, Vol. 13609).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis
Selvan, Raghav, Bhagwat, N., Anthony, L. F. W., Kanding, B. & Dam, Erik Bjørnager, 2022, Medical Image Computing and Computer Assisted Intervention – MICCAI 2022: 25th International Conference Singapore, September 18–22, 2022 Proceedings, Part V. Springer, p. 506–516 (Lecture Notes in Computer Science, Vol. 13435).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2021
- Published
Deep ensemble model for segmenting microscopy images in the presence of limited labeled data
Kaminski, J. M., Allodi, I., Montañana-Rosell, Roser, Selvan, Raghav & Kiehn, O., 2021, International Conference on Medical Imaging with Deep Learning, MIDL (Short Paper). 3 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Segmenting Two-Dimensional Structures with Strided Tensor Networks
Selvan, Raghav, Dam, Erik Bjørnager & Petersen, Jens, 2021, Information Processing in Medical Imaging - 27th International Conference, IPMI 2021, Proceedings. Feragen, A., Sommer, S., Schnabel, J. & Nielsen, M. (eds.). Springer, p. 401-414 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12729 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2020
- Published
Tensor Networks for Medical Image Classification
Selvan, Raghav & Dam, Erik Bjørnager, 21 Apr 2020, International Conference on Medical Imaging with Deep Learning, MIDL 2020, 6-8 July 2020, Montréal, QC, Canada. PMLR, p. 721-732 (Proceedings of Machine Learning Research, Vol. 121).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Uncertainty quantification in medical image segmentation with normalizing flows
Selvan, Raghav, Faye, F., Middleton, Jon Anthony & Pai, A., 2020, Machine Learning in Medical Imaging: 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings. Springer, 12 p. (Lecture Notes in Computer Science, Vol. 12436).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2019
- Published
A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs
Juarez, A. G., Selvan, Raghav, Saghir, Zaigham & de Bruijne, Marleen, 22 Aug 2019, Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings. Springer, p. 583-591 (Lecture Notes in Computer Science, Vol. LNCS 11861).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
ID: 144763853
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479
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Extraction of Airways from Volumetric Data
Research output: Book/Report › Ph.D. thesis › Research
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239
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Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
187
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Segmentation of roots in soil with U-Net
Research output: Contribution to journal › Journal article › Research › peer-review
Published