دورية أكاديمية
A Label-Efficient Framework for Automated Sinonasal CT Segmentation in Image-Guided Surgery.
| العنوان: | A Label-Efficient Framework for Automated Sinonasal CT Segmentation in Image-Guided Surgery. |
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| المؤلفون: | Sahu, Manish, Xiao, Yuliang, Porras, Jose L, Amanian, Ameen, Jain, Aseem, Thamboo, Andrew, Taylor, Russell H, Creighton, Francis X, Ishii, Masaru |
| المصدر: | Otolaryngol Head Neck Surg ; ISSN:1097-6817 |
| بيانات النشر: | Wiley |
| سنة النشر: | 2024 |
| المجموعة: | PubMed Central (PMC) |
| مصطلحات موضوعية: | automated segmentation and registration, deep learning, image‐guided surgery, medical image segmentation, semi‐supervised learning, sinonasal computed tomography |
| الوصف: | Segmentation, the partitioning of patient imaging into multiple, labeled segments, has several potential clinical benefits but when performed manually is tedious and resource intensive. Automated deep learning (DL)-based segmentation methods can streamline the process. The objective of this study was to evaluate a label-efficient DL pipeline that requires only a small number of annotated scans for semantic segmentation of sinonasal structures in CT scans. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| العلاقة: | https://doi.org/10.1002/ohn.868Test; https://pubmed.ncbi.nlm.nih.gov/38922721Test |
| DOI: | 10.1002/ohn.868 |
| الإتاحة: | https://doi.org/10.1002/ohn.868Test https://pubmed.ncbi.nlm.nih.gov/38922721Test |
| حقوق: | © 2024 American Academy of Otolaryngology–Head and Neck Surgery Foundation. |
| رقم الانضمام: | edsbas.4BC9AA32 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1002/ohn.868 |
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