3D Nuclei Segmentation by Combining GAN Based Image Synthesis and Existing 3D Manual Annotations
Xareni Galindo,
Thierno Barry,
Pauline Guyot
et al.
Abstract:Nuclei segmentation is an important task in cell biology analysis that requires accurate and reliable methods, especially within complex low signal to noise ratio images with crowded cells populations. In this context, deep learning-based methods such as Stardist have emerged as the best performing solutions for segmenting nucleus. Unfortunately, the performances of such methods rely on the availability of vast libraries of ground truth hand-annotated data-sets, which become especially tedious to create for 3D… Show more
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