دورية أكاديمية
Automatic segmentation of whole-slide H&E stained breast histopathology images using a deep convolutional neural network architecture
| العنوان: | Automatic segmentation of whole-slide H&E stained breast histopathology images using a deep convolutional neural network architecture |
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| المؤلفون: | Priego Torres, Blanca María, Sánchez Morillo, Daniel, Fernández Granero, Miguel Ángel, García-Rojo, Marcial |
| المساهمون: | Anatomía Patológica, Biología Celular, Histología, Historia de la Ciencia, Medicina Legal y Forense y Toxicología, Ingeniería en Automática, Electrónica, Arquitectura y Redes de Computadores |
| المصدر: | Expert Systems with Applications, Volume 151, 113387 |
| بيانات النشر: | PERGAMON-ELSEVIER SCIENCE LTD |
| سنة النشر: | 2024 |
| المجموعة: | RODIN - Repositorio de Objetos de Docencia e Investigación de la Universidad de Cádiz |
| مصطلحات موضوعية: | Breast cancer, Deep learning, H&E staining, Segmentation, Whole-Slide Imaging |
| الوصف: | This version of the article was accepted for publication, after peer review and does not reflect post-acceptance improvements, or any corrections. The published version is available online (2020-03-18) at: https://doi.org/10.1016/j.eswa.2020.113387Test. ; In this research, we propose a processing pipeline for the automatic segmentation of stained BC images presenting different types of histopathological patterns. Experimental results on a collection of patches of breast cancer images demonstrate how the designed processing pipeline performs properly regardless of the size, texture or any other colour-shape features typical of the malignant carcinomas considered in this study. The estimated segmentation accuracy and frequency-weighted intersection over union ( FWIoU ) were 95.62%, 92.52%, respectively. Additionally, a web-based platform which includes a slide-viewer and an annotation tool was developed. The automatic segmentation method proposed in this work was integrated into this platform and currently, it is being used as a decision-support tool by pathologists. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 0957-4174 |
| العلاقة: | info:eu-repo/grantAgreement/Junta de Andalucía//PI0032-2017; http://hdl.handle.net/10498/30087Test |
| DOI: | 10.1016/J.ESWA.2020.113387 |
| الإتاحة: | https://doi.org/10.1016/J.ESWA.2020.113387Test http://hdl.handle.net/10498/30087Test |
| حقوق: | Attribution-NonCommercial-NoDerivatives 4.0 Internacional ; http://creativecommons.org/licenses/by-nc-nd/4.0Test/ ; open access |
| رقم الانضمام: | edsbas.E4A17FA5 |
| قاعدة البيانات: | BASE |
| تدمد: | 09574174 |
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| DOI: | 10.1016/J.ESWA.2020.113387 |