most citedHoVer-UNet: Accelerating HoVerNet with UNet-based multi-class nuclei segmentation via knowledge distillation

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

eess.IV2024

NuLite -- Lightweight and Fast Model for Nuclei Instance Segmentation and Classification

Cristian Tommasino, Cristiano Russo, Antonio Maria Rinaldi

In pathology, accurate and efficient analysis of Hematoxylin and Eosin (H\&E) slides is crucial for timely and effective cancer diagnosis. Although many deep learning solutions for…

eess.IV2023★ 2 cited

HoVer-UNet: Accelerating HoVerNet with UNet-based multi-class nuclei segmentation via knowledge distillation

Cristian Tommasino, Cristiano Russo, Antonio Maria Rinaldi +1

We present HoVer-UNet, an approach to distill the knowledge of the multi-branch HoVerNet framework for nuclei instance segmentation and classification in histopathology. We propose…