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Shodai Taguchi on Muck Rack

Shodai Taguchi

As seen in: BioRxiv
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Articles

Deep Learning Pipeline for Segmentation and Quantification of Overlapping Membranes in 2D Image

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By Keita Chagi, Hiroki Kawai, Kenji Irie, Shodai Taguchi
| BioRxiv
Abstract Quantitative morphological analysis is crucial for understanding cellular processes. While 3D Z-stack imaging offers high-resolution data, the complexity of 3D structures makes direct interpretation and manual annotation challenging and time-consuming, especially for large datasets.
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