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of 8
pro vyhledávání: '"Utz, Jonas"'
Autor:
Qiu, Jingna, Aubreville, Marc, Wilm, Frauke, Öttl, Mathias, Utz, Jonas, Schlereth, Maja, Breininger, Katharina
Acquiring annotations for whole slide images (WSIs)-based deep learning tasks, such as creating tissue segmentation masks or detecting mitotic figures, is a laborious process due to the extensive image size and the significant manual work involved in
Externí odkaz:
http://arxiv.org/abs/2407.06363
Autor:
Thies, Mareike, Maul, Noah, Mei, Siyuan, Pfaff, Laura, Vysotskaya, Nastassia, Gu, Mingxuan, Utz, Jonas, Possart, Dennis, Folle, Lukas, Wagner, Fabian, Maier, Andreas
Motion artifacts can compromise the diagnostic value of computed tomography (CT) images. Motion correction approaches require a per-scan estimation of patient-specific motion patterns. In this work, we train a score-based model to act as a probabilit
Externí odkaz:
http://arxiv.org/abs/2404.14747
Autor:
Utz, Jonas, Weise, Tobias, Schlereth, Maja, Wagner, Fabian, Thies, Mareike, Gu, Mingxuan, Uderhardt, Stefan, Breininger, Katharina
Annotating nuclei in microscopy images for the training of neural networks is a laborious task that requires expert knowledge and suffers from inter- and intra-rater variability, especially in fluorescence microscopy. Generative networks such as Cycl
Externí odkaz:
http://arxiv.org/abs/2308.01769
Autor:
Wagner, Fabian, Thies, Mareike, Pfaff, Laura, Maul, Noah, Pechmann, Sabrina, Gu, Mingxuan, Utz, Jonas, Aust, Oliver, Weidner, Daniela, Neag, Georgiana, Uderhardt, Stefan, Choi, Jang-Hwan, Maier, Andreas
Self-supervised image denoising techniques emerged as convenient methods that allow training denoising models without requiring ground-truth noise-free data. Existing methods usually optimize loss metrics that are calculated from multiple noisy reali
Externí odkaz:
http://arxiv.org/abs/2212.04832
Autor:
Thies, Mareike, Wagner, Fabian, Maul, Noah, Folle, Lukas, Meier, Manuela, Rohleder, Maximilian, Schneider, Linda-Sophie, Pfaff, Laura, Gu, Mingxuan, Utz, Jonas, Denzinger, Felix, Manhart, Michael, Maier, Andreas
Incorporating computed tomography (CT) reconstruction operators into differentiable pipelines has proven beneficial in many applications. Such approaches usually focus on the projection data and keep the acquisition geometry fixed. However, precise k
Externí odkaz:
http://arxiv.org/abs/2212.02177
Autor:
Wagner, Fabian, Thies, Mareike, Pfaff, Laura, Aust, Oliver, Pechmann, Sabrina, Weidner, Daniela, Maul, Noah, Rohleder, Maximilian, Gu, Mingxuan, Utz, Jonas, Denzinger, Felix, Maier, Andreas
Computed tomography (CT) is routinely used for three-dimensional non-invasive imaging. Numerous data-driven image denoising algorithms were proposed to restore image quality in low-dose acquisitions. However, considerably less research investigates m
Externí odkaz:
http://arxiv.org/abs/2211.01111
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Akademický článek
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