دورية أكاديمية
Automatic detect lung node with deep learning in segmentation and imbalance data labeling
| العنوان: | Automatic detect lung node with deep learning in segmentation and imbalance data labeling |
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| المؤلفون: | Ting-Wei Chiu, Yu-Lin Tsai, Shun-Feng Su |
| المصدر: | Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021) |
| بيانات النشر: | Nature Portfolio, 2021. |
| سنة النشر: | 2021 |
| المجموعة: | LCC:Medicine LCC:Science |
| مصطلحات موضوعية: | Medicine, Science |
| الوصف: | Abstract In this study, a novel method with the U-Net-based network architecture, 2D U-Net, is employed to segment the position of lung nodules, which are an early symptom of lung cancer and have a high probability of becoming a carcinoma, especially when a lung nodule is bigger than 15 $$\mathrm{mm}^2$$ mm 2 . A serious problem of considering deep learning for all medical images is imbalanced labeling between foreground and background. The lung nodule is the foreground which accounts for a lower percentage in a whole image. The evaluation function adopted in this study is dice coefficient loss, which is usually used in image segmentation tasks. The proposed pre-processing method in this study is to use complementary labeling as the input in U-Net. With this method, the labeling is swapped. The no-nodule position is labeled. And the position of the nodule becomes non-labeled. The result shows that the proposal in this study is efficient in a small quantity of data. This method, complementary labeling could be used in a small data quantity scenario. With the use of ROI segmentation model in the data pre-processing, the results of lung nodule detection can be improved a lot as shown in the experiments. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2045-2322 |
| Relation: | https://doaj.org/toc/2045-2322 |
| DOI: | 10.1038/s41598-021-90599-4 |
| URL الوصول: | https://doaj.org/article/b06b32aa28454d3185a755c627a8e2e6 |
| رقم الأكسشن: | edsdoj.b06b32aa28454d3185a755c627a8e2e6 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 20452322 |
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| DOI: | 10.1038/s41598-021-90599-4 |