Academic Journal
Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning
| العنوان: | Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning |
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| المؤلفون: | Fernando Pérez-Cota, Giovanna Martínez-Arellano, Salvatore La Cavera, William Hardiman, Luke Thornton, Rafael Fuentes-Domínguez, Richard J. Smith, Alan McIntyre, Matt Clark |
| المصدر: | Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023) |
| بيانات النشر: | Nature Portfolio, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Medicine LCC:Science |
| مصطلحات موضوعية: | Medicine, Science |
| الوصف: | Abstract There is a consensus about the strong correlation between the elasticity of cells and tissue and their normal, dysplastic, and cancerous states. However, developments in cell mechanics have not seen significant progress in clinical applications. In this work, we explore the possibility of using phonon acoustics for this purpose. We used phonon microscopy to obtain a measure of the elastic properties between cancerous and normal breast cells. Utilising the raw time-resolved phonon-derived data (300 k individual inputs), we employed a deep learning technique to differentiate between MDA-MB-231 and MCF10a cell lines. We achieved a 93% accuracy using a single phonon measurement in a volume of approximately 2.5 μm3. We also investigated means for classification based on a physical model that suggest the presence of unidentified mechanical markers. We have successfully created a compact sensor design as a proof of principle, demonstrating its compatibility for use with needles and endoscopes, opening up exciting possibilities for future applications. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2045-2322 |
| Relation: | https://doaj.org/toc/2045-2322 |
| DOI: | 10.1038/s41598-023-42793-9 |
| URL الوصول: | https://doaj.org/article/42397df69f224730aa028e2626112e27 |
| رقم الانضمام: | edsdoj.42397df69f224730aa028e2626112e27 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20452322 |
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| DOI: | 10.1038/s41598-023-42793-9 |