A U-Net architecture with specialized boundary attention decoder, built on pathology foundation models, reports higher Dice and IoU scores than prior methods for glomeruli segmentation.
A hybrid cnn-transxnet approach for advanced glomerular segmentation in renal histology imaging
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A deep learning framework for glomeruli segmentation with boundary attention
A U-Net architecture with specialized boundary attention decoder, built on pathology foundation models, reports higher Dice and IoU scores than prior methods for glomeruli segmentation.