{"ID":2851297,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.20754","arxiv_id":"2510.20754","title":"ACS-SegNet: An Attention-Based CNN-SegFormer Segmentation Network for Tissue Segmentation in Histopathology","abstract":"Automated histopathological image analysis plays a vital role in computer-aided diagnosis of various diseases. Among developed algorithms, deep learning-based approaches have demonstrated excellent performance in multiple tasks, including semantic tissue segmentation in histological images. In this study, we propose a novel approach based on attention-driven feature fusion of convolutional neural networks (CNNs) and vision transformers (ViTs) within a unified dual-encoder model to improve semantic segmentation performance. Evaluation on two publicly available datasets showed that our model achieved μIoU/μDice scores of 76.79%/86.87% on the GCPS dataset and 64.93%/76.60% on the PUMA dataset, outperforming state-of-the-art and baseline benchmarks. The implementation of our method is publicly available in a GitHub repository: https://github.com/NimaTorbati/ACS-SegNet","short_abstract":"Automated histopathological image analysis plays a vital role in computer-aided diagnosis of various diseases. Among developed algorithms, deep learning-based approaches have demonstrated excellent performance in multiple tasks, including semantic tissue segmentation in histological images. In this study, we propose a...","url_abs":"https://arxiv.org/abs/2510.20754","url_pdf":"https://arxiv.org/pdf/2510.20754v1","authors":"[\"Nima Torbati\",\"Anastasia Meshcheryakova\",\"Ramona Woitek\",\"Diana Mechtcheriakova\",\"Amirreza Mahbod\"]","published":"2025-10-23T17:21:06Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[\"Vision Transformer\",\"Transformer\",\"Convolutional Neural Network\"]","has_code":false,"code_links":[{"ID":607887,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2851297,"paper_url":"https://arxiv.org/abs/2510.20754","paper_title":"ACS-SegNet: An Attention-Based CNN-SegFormer Segmentation Network for Tissue Segmentation in Histopathology","repo_url":"https://github.com/NimaTorbati/ACS-SegNet","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}