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2020 – today
- 2024
[c5]Maximilian Fischer, Peter Neher, Peter J. Schüffler, Shuhan Xiao, Silvia Dias Almeida, Constantin Ulrich, Alexander Muckenhuber, Rickmer Braren, Michael Götz, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein:
Abstract: Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning. Bildverarbeitung für die Medizin 2024: 158- [i1]Maximilian Fischer, Peter Neher, Tassilo Wald, Silvia Dias Almeida, Shuhan Xiao, Peter J. Schüffler, Rickmer Braren, Michael Götz, Alexander Muckenhuber, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein:
Learned Image Compression for HE-stained Histopathological Images via Stain Deconvolution. CoRR abs/2406.12623 (2024) - 2023
- [c4]Maximilian Fischer, Peter Neher
, Michael Götz, Shuhan Xiao, Silvia Dias Almeida, Peter J. Schüffler, Alexander Muckenhuber, Rickmer Braren, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein:
Abstract: Deep-learning on Lossily Compressed Pathology Images - Adverse Effects for ImageNet Pre-trained Models. Bildverarbeitung für die Medizin 2023: 245 - [c3]Maximilian Fischer, Peter Neher, Peter J. Schüffler, Shuhan Xiao, Silvia Dias Almeida, Constantin Ulrich, Alexander Muckenhuber, Rickmer Braren, Michael Götz, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein:
Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning. MLMI@MICCAI (2) 2023: 427-436 - 2022
- [c2]Maximilian Fischer, Philipp Schader, Rickmer Braren, Michael Götz, Alexander Muckenhuber, Wilko Weichert, Peter J. Schüffler, Jens Kleesiek, Jonas Scherer, Klaus Kades, Klaus H. Maier-Hein, Marco Nolden:
DICOM Whole Slide Imaging for Computational Pathology Research in Kaapana and the Joint Imaging Platform. Bildverarbeitung für die Medizin 2022: 273-278 - [c1]Maximilian Fischer, Peter Neher, Michael Götz, Shuhan Xiao, Silvia Dias Almeida, Peter J. Schüffler, Alexander Muckenhuber, Rickmer Braren, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein:
Deep Learning on Lossily Compressed Pathology Images: Adverse Effects for ImageNet Pre-trained Models. MOVI@MICCAI 2022: 73-83
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