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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
Tim Scherr1, Katharina Löffler1,2, Moritz Böhland1
1Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany.
This study introduces a novel method for segmenting and tracking touching cells in microscopy images, improving accuracy even with low signal-to-noise ratios. The approach enhances cell tracking by incorporating movement estimation, achieving top rankings in a challenge.
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