A Comparative Analysis of SegFormer, FabE-Net and VGG-UNet Models for the Segmentation of Neural Structures on Histological Sections

<b>Background:</b> Segmenting nerve fibres in histological images is a tricky job because of how much the tissue looks can change. Modern neural network architectures, including U-Net and transformers, demonstrate varying degrees of effectiveness in this area. The aim of this study is to conduct a c...

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Autors principals:	Igor Makarov, Elena Koshevaya, Alina Pechenina, Galina Boyko, Anna Starshinova, Dmitry Kudlay, Taiana Makarova, Lubov Mitrofanova
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2025-09-01
Col·lecció:	Diagnostics
Matèries:	digital pathology convolutional neural networks segmentation of histological images segmentation of nerve fibres visual transformers
Accés en línia:	https://www.mdpi.com/2075-4418/15/18/2408
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