Segmented Masks for Best-Performing Models in A U-Net-Based Approach for Histological Tissue Segmentation Using RCAug Data Augmentation

Authors: Lucas Latorre de Oliveira, Domingos; Tosta, Thaína; Neves, Leandro Alves; Silva, Adriano; Martins, Alessandro Santana; de Faria, Paulo Rogério; Zanchetta do Nascimento, Marcelo;

doi: 10.5281/zenodo.17754088 , 10.5281/zenodo.17754089

Segmented Masks for Best-Performing Models in A U-Net-Based Approach for Histological Tissue Segmentation Using RCAug Data Augmentation

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Abstract

This dataset contains the segmentation masks corresponding to the best-performing model and augmentation configurations reported in the paper “A U-Net-Based Approach for Histological Tissue Segmentation Using RCAug Data Augmentation” (SIBGRAPI 2025, IEEE Xplore). For each histology dataset, we provide the predicted masks generated by the top-performing U-Net-based models under the augmentation strategies highlighted in the article, together with concise summary metrics. These files are intended to support result inspection, comparison and reuse in further studies.

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