Johan Öfverstedt
Researcher at Department of Information Technology, Vi3; Image Analysis
- Email:
- johan.ofverstedt[AT-sign]it.uu.se
- Visiting address:
- Room
POL 104237 hus 10, Lägerhyddsvägen 1
- Postal address:
- Box 337
751 05 UPPSALA
Postdoctoral position
at
Department of Surgical Sciences, Radiology
- Email:
- johan.ofverstedt[AT-sign]uu.se
- Visiting address:
- Akademiska sjukhuset, ingång 70, 1tr
- Postal address:
- Akademiska sjukhuset, ingång 70, 1tr
751 85 UPPSALA
Short presentation
I am a postdoctoral researcher in the PET/MR research group headed by Professor Joel Kullberg and Professor Håkan Ahlström where I am researching topics related to medical image registration and deep image regression.
My PhD research was in method development for efficient fusion of intensity and spatial information, distance/similarity measures between sets/images, image registration, and machine learning methods.
Keywords: image analysis machine learning deep learning optimization robustness similarity measures image registration distance transforms
Reviewed publications
2021
L Solorzano, L. Wik, T. O. Bontell, Y. Wang, A. H. Klemm, J. Öfverstedt, A. S. Jakola, A. Östman, C. Wählby: Machine learning for cell classification and neighborhood analysis in glioma tissue. Cytometry Part A, 2021.
2020
N. Pielawski, E. Wetzer, J. Öfverstedt, J. Lu, C. Wählby, J. Lindblad, and N. Sladoje. CoMIR: Contrastive Multimodal Image Representations for Registration. NeurIPS 2020.
J. Öfverstedt, J. Lindblad, and N. Sladoje. Stochastic Distance Transform: Theory, Algorithms, and Applications. Journal of Mathematical Imaging and Vision, 62(5), 751-769, 2020. (Online - Open Access/CC BY)
2019
J. Öfverstedt, J. Lindblad, and N. Sladoje. Stochastic Distance Transform. (Preprint - arXiv:1810.08097 [cs.CV]). In Proceedings of the 21th international conference on Discrete Geometry for Computer Imagery (DGCI), Lecture Notes in Computer Science, LNCS-11134, pp. 75--86, Paris, France, March 2019. (Online).
J. Öfverstedt, J. Lindblad, and N. Sladoje. Fast and Robust Symmetric Image Registration Based on Distances Combining Intensity and Spatial Information. IEEE Transactions on Image Processing, Vol. 27, No. 7, pp. 3584-3597, 2019. (Online - Open Access/CC BY) (Preprint - arXiv:1807.11599 [cs.CV]).
2017
J. Öfverstedt, N. Sladoje, and J. Lindblad. Distance Between Vector-valued Fuzzy Sets based on Intersection Decomposition with Applications in Object Detection. In Proc. of the 13th International Symposium on Mathematical Morphology, ISMM2017, Fontainebleau, France, Lecture Notes in Computer Science, LNCS-10225, pp. 395-407, Springer 2017.
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