Jon Anthony Middleton
Industrial PhD
Image Analysis, Computational Modelling and Geometry
Universitetsparken 1, 2100 København Ø
- 2024
- Published
Local Gamma Augmentation for Ischemic Stroke Lesion Segmentation on MRI
Middleton, Jon Anthony, Bauer, Marko, Johansen, Jacob, Perslev, Mathias, Sheng, K., Ingala, S., Nielsen, Mads & Pai, A., 2024, Proceedings of the 5th Northern Lights Deep Learning Conference ({NLDL}). PMLR, p. 158-164 (Proceedings of Machine Learning Research, Vol. 233).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2023
- Published
Instance-Specific Augmentation of Brain MRIs with Variational Autoencoders
Middleton, Jon Anthony, Bauer, Marko, Johansen, Jacob, Nielsen, Mads, Sommer, Stefan Horst & Pai, A. S. U., 2023, Medical Applications with Disentanglements : First MICCAI Workshop, MAD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Springer, p. 49-58 (Lecture Notes in Computer Science, Vol. 13823).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2022
- Published
Automated Identification of Multiple Findings on Brain MRI for Improving Scan Acquisition and Interpretation Workflows: A Systematic Review
Sheng, K., Offersen, C. M., Middleton, Jon Anthony, Carlsen, Jonathan Frederik, Truelsen, Thomas Clement, Pai, A., Johansen, Jacob & Nielsen, Michael Bachmann, Aug 2022, In: Diagnostics. 12, 8, 19 p., 1878.Research output: Contribution to journal › Review › Research › peer-review
- 2021
- Published
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
Jimenez-Solem, E., Petersen, T. S., Hansen, C., Hansen, C., Lioma, C., Igel, C., Boomsma, W., Krause, O., Lorenzen, S., Selvan, R., Petersen, J., Nyeland, M. E., Ankarfeldt, M. Z., Virenfeldt, G. M., Winther-Jensen, M., Linneberg, A., Ghazi, M. M., Detlefsen, N., Lauritzen, A. D., Smith, A. G. & 15 others, , 2021, In: Scientific Reports. 11, 1, 12 p., 3246.Research output: Contribution to journal › Journal article › Research › peer-review
- 2020
- 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
ID: 230170193
Most downloads
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272
downloads
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 -
36
downloads
Uncertainty quantification in medical image segmentation with normalizing flows
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Published -
20
downloads
Automated Identification of Multiple Findings on Brain MRI for Improving Scan Acquisition and Interpretation Workflows: A Systematic Review
Research output: Contribution to journal › Review › Research › peer-review
Published