Research output per year
Research output per year
Unit profile
Research
The Mathematical Imaging Group is a research group within the Centre for Mathematical Sciences. We are developing new mathematical methods for problems arising in imaging and computer vision. In terms of mathematical tools, we are currently focused on optimization methods, polynomial equations, inverse problems, large scale computing and graph theory. We address problems in geometric computer vision, medical image analysis, cognition and image analysis. We are frequently collaborating with academic partners, industry and society at large.
UKÄ subject classification
- Computer Vision and Robotics (Autonomous Systems)
- Medical Image Processing
- Radiology, Nuclear Medicine and Medical Imaging
- Geometry
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
Profiles
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Håkan Ardö
- Mathematics (Faculty of Engineering) - Senior lecturer
- Mathematical Imaging Group
Person: Academic
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Kalle Åström
- LU Profile Area: Natural and Artificial Cognition - Coordinator
- LTH Profile Area: Pillars of AI and Digitalization - Profile area member
- ELLIIT: the Linköping-Lund initiative on IT and mobile communication - Professor
- eSSENCE: The e-Science Collaboration - Principal investigator
- Stroke Imaging Research group - Professor
- Mathematics (Faculty of Engineering) - Professor
Person: Academic
Research output
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Active and Physics-Based Human Pose Reconstruction
Gärtner, E., 2023, Lund: Department of Computer Science, Lund University.Research output: Thesis › Doctoral Thesis (compilation)
Open AccessFile -
Applications in Monocular Computer Vision using Geometry and Learning: Map Merging, 3D Reconstruction and Detection of Geometric Primitives
Gillsjö, D., 2023, Lund: Lund University / Centre for Mathematical Sciences /LTH.Research output: Thesis › Doctoral Thesis (compilation)
Open AccessFile -
Classification of point-of-care ultrasound in breast imaging using deep learning
Karlsson, J., Arvidsson, I., Sahlin, F., Åström, K., Overgaard, N. C., Lång, K. & Heyden, A., 2023, Medical Imaging 2023: Computer-Aided Diagnosis. Iftekharuddin, K. M. & Chen, W. (eds.). SPIE, 124650Y. (Proceedings of SPIE; vol. 12465).Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review
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Deep learning based evaluation of coronary artery disease and estimation of quantitative coronary angiography using myocardial perfusion imaging
Arvidsson, I., Ochoa-Figueroa, M., Åström, K., Heyden, A. & Overgaard, N. C.
2023/01/01 → 2024/12/31
Project: Research
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eSSENCE@LU 8:7 - Breast cancer diagnosis using pocket-sized ultrasound device and Deep Learning
Heyden, A., Lång, K., Karlsson, J., Arvidsson, I., Overgaard, N. C. & Åström, K.
2022/01/01 → 2023/12/31
Project: Research
Activities
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Tutorial "Camera Geometry Problems in Computer Vision" at ICCV 2023
Viktor Larsson (Organiser), Zuzana Kukelova (Organiser), Tomas Pajdla (Organiser), Daniel Barath (Organiser) & Torsten Sattler (Organiser)
2023 Oct 2Activity: Participating in or organising an event › Organisation of workshop/ seminar/ course
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Invited Plenary talk "Localization and Mapping from Images" at SIAM AG 2023
Viktor Larsson (Keynote/plenary speaker)
2023 Jul 12Activity: Talk or presentation › Invited talk
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TV4 morning show - participated in a segment on deep fakes
Kalle Åström (Role not specified)
2023 Jun 22Activity: Other › Media participation
Prizes and distinction
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Best Student Paper (ICCV21)
Lindenberger, Philipp (Recipient), Sarlin, Paul-Edouard (Recipient), Larsson, Viktor (Recipient) & Pollefeys, Marc (Recipient), 2021
Prize: Prize (including medals and awards)
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Best Paper Award (ACCV18)
Pritts, James (Recipient), Kukelova, Zuzana (Recipient), Larsson, Viktor (Recipient) & Chum, Ondrej (Recipient), 2018
Prize: Prize (including medals and awards)
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