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Prof. Koen Van Leemput
Professor at Technical University of Denmark
SPIE Involvement:
Conference Program Committee | Author
Publications (5)
Proceedings Article | 9 March 2018 Presentation + Paper
CT metal artifact reduction using MR image patches
Jonathan Nielsen, Jens Edmund, Koen Van Leemput
Proceedings Volume 10573, 105730P (2018) https://doi.org/10.1117/12.2293815
KEYWORDS: Magnetic resonance imaging, Reconstruction algorithms, Computed tomography, X-ray computed tomography, Expectation maximization algorithms, Radiotherapy, Image quality
Proceedings Article | 2 March 2018 Paper
Skull segmentation from MR scans using a higher-order shape model based on convolutional restricted Boltzmann machines
Oula Puonti, Koen Van Leemput, Jesper Nielsen, Christian Bauer, Hartwig Roman Siebner, Kristoffer Madsen, Axel Thielscher
Proceedings Volume 10574, 1057404 (2018) https://doi.org/10.1117/12.2293073
KEYWORDS: Skull, Data modeling, Tissues, Image segmentation, Head, Magnetic resonance imaging, Computed tomography, Brain, Mars, Brain stimulation
Proceedings Article | 27 February 2018 Paper
An automatically generated texture-based atlas of the lungs
Yashin Dicente Cid, Oula Puonti, Alexandra Platon, Koen Van Leemput, Henning Müller, Pierre-Alexandre Poletti
Proceedings Volume 10575, 105753A (2018) https://doi.org/10.1117/12.2294004
KEYWORDS: Lung, Computed tomography, Databases, Image segmentation, Visualization, Pulmonary hypertension, Spatial analysis, Chest
Proceedings Article | 21 March 2016 Paper
Computed tomography synthesis from magnetic resonance images in the pelvis using multiple random forests and auto-context features
Daniel Andreasen, Jens Edmund, Vasileios Zografos, Bjoern Menze, Koen Van Leemput
Proceedings Volume 9784, 978417 (2016) https://doi.org/10.1117/12.2216924
KEYWORDS: Magnetic resonance imaging, Computed tomography, Radiotherapy, Machine learning, Algorithm development, Feature extraction, Data modeling, Tissues, Scanners, Rutherfordium
Proceedings Article | 21 March 2016 Paper
A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients
Mikael Agn, Ian Law, Per Munck af Rosenschöld, Koen Van Leemput
Proceedings Volume 9784, 97841D (2016) https://doi.org/10.1117/12.2216814
KEYWORDS: Brain cancer, Image segmentation, Brain, Radiotherapy, Tissues, Performance modeling, Magnetic resonance imaging, Scanners, Image analysis, Tumors, Data modeling, Expectation maximization algorithms, Computed tomography, Electroluminescent displays
Conference Committee Involvement (12)
Image Processing
16 February 2025 | San Diego, California, United States
Image Processing
19 February 2024 | San Diego, California, United States
Image Processing
20 February 2023 | San Diego, California, United States
Image Processing
20 February 2022 | San Diego, California, United States
Image Processing
15 February 2021 | Online Only, California, United States
Showing 5 of 12 Conference Committees
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