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Glomeruli detection and classification in histopathological images using deep learning semantic segmentation | Synapse
March 3, 2026
Open Access
Glomeruli detection and classification in histopathological images using deep learning semantic segmentation
PJ
Pablo Juan-Ferrer
Universitat Jaume I
NP
Nayara Pérez-Sánchez
Fundación Instituto Valenciano de Oncología
FP
Filiberto Pla
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Puntos clave
Detection and classification of glomeruli showed a significant improvement in accuracy with deep learning methods.
The deep learning model achieved an accuracy of 92% in identifying glomeruli in histopathological images.
Using semantic segmentation, the model was trained on a dataset of annotated images to enhance classification reliability.
The findings support the potential for AI-based tools in histopathology, though external validation is necessary.
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Juan-Ferrer et al. (Wed,) studied this question.
synapsesocial.com/papers/69a75ab9c6e9836116a20e93
https://doi.org/https://doi.org/10.1186/s12880-026-02178-6
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