Universitas Yudharta Pasuruan, Lukman Hakim (2020) Transfer Learning by Cascaded Network to Identify and Classify Lung Nodules for Cancer Detection. Springer Link, 1212.
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Cek Plagiasi-Transfer Learning by Cascaded Network to identify and classify lung nodules for cancer detection.pdf Download (1MB) |
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Transfer Learning by Cascaded Network to identify and classify lung nodules for cancer detection.pdf Download (840kB) |
Abstract
Lung cancer is one of the most deadly diseases in the world. Detecting such tumors at an early stage can be a tedious task. Existing deep learning architecture for lung nodule identification used complex architecture with large number of parameters. This study developed a cascaded architecture which can accurately segment and classify the benign or malignant lung nodules on computed tomography (CT) images. The main contribution of this study is to introduce a segmentation network where the first stage trained on a public data set can help to recognize the images which included a nodule from any data set by means of transfer learning. And the segmentation of a nodule improves the second stage to classify the nodules into benign and malignant. The proposed architecture outperformed the conventional methods with an area under curve value of 95.67%. The experimental results showed that the classification accuracy of 97.96% of our proposed architecture outperformed other simple and complex architectures in classifying lung nodules for lung cancer detection.
| Item Type: | Article | ||||||
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| Subjects: | Teknologi & Ilmu Terapan > Ilmu Teknik dan Ilmu yang Berkaitan | ||||||
| Divisions: | Fakultas Teknik > Teknik Informatika | ||||||
| Date Deposited: | 25 Oct 2023 04:45 | ||||||
| Last Modified: | 25 Oct 2023 04:45 | ||||||
| URI: | https://repository.yudharta.ac.id/id/eprint/3203 |
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