دورية أكاديمية
Assessment of image quality and impact of deep learning-based software in non-contrast head CT scans
| العنوان: | Assessment of image quality and impact of deep learning-based software in non-contrast head CT scans |
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| المؤلفون: | Denise Bos, Aydin Demircioğlu, Julia Neuhoff, Johannes Haubold, Sebastian Zensen, Marcel K. Opitz, Marcel A. Drews, Yan Li, Hanna Styczen, Michael Forsting, Kai Nassenstein |
| المصدر: | Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024) |
| بيانات النشر: | Nature Portfolio, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Medicine LCC:Science |
| مصطلحات موضوعية: | Medicine, Science |
| الوصف: | Abstract In this retrospective study, we aimed to assess the objective and subjective image quality of different reconstruction techniques and a deep learning-based software on non-contrast head computed tomography (CT) images. In total, 152 adult head CT scans (77 female, 75 male; mean age 69.4 ± 18.3 years) obtained from three different CT scanners using different protocols between March and April 2021 were included. CT images were reconstructed using filtered-back projection (FBP), iterative reconstruction (IR), and post-processed using a deep learning-based algorithm (PS). Post-processing significantly reduced noise in FBP-reconstructed images (up to 15.4% reduction) depending on the protocol, leading to improvements in signal-to-noise ratio of up to 19.7%. However, when deep learning-based post-processing was applied to FBP images compared to IR alone, the differences were inconsistent and partly non-significant, which appeared to be protocol or site specific. Subjective assessments showed no significant overall improvement in image quality for all reconstructions and post-processing. Inter-rater reliability was low and preferences varied. Deep learning-based denoising software improved objective image quality compared to FBP in routine head CT. A significant difference compared to IR was observed for only one protocol. Subjective assessments did not indicate a significant clinical impact in terms of improved subjective image quality, likely due to the low noise levels in full-dose images. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2045-2322 |
| العلاقة: | https://doaj.org/toc/2045-2322Test |
| DOI: | 10.1038/s41598-024-62394-4 |
| الوصول الحر: | https://doaj.org/article/ee83d3ee26bf46f1bbc8d5fe19deb44eTest |
| رقم الانضمام: | edsdoj.83d3ee26bf46f1bbc8d5fe19deb44e |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20452322 |
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| DOI: | 10.1038/s41598-024-62394-4 |