Segmentation of Chest X-Ray Images Using U-Net Model
| dc.contributor.author | Kamil, Mohammed Y. | |
| dc.contributor.author | Hashem, Sahar A. | |
| dc.coverage.issue | 2 | cs |
| dc.coverage.volume | 28 | cs |
| dc.date.accessioned | 2023-01-13T06:21:06Z | |
| dc.date.available | 2023-01-13T06:21:06Z | |
| dc.date.issued | 2022-12-20 | cs |
| dc.description.abstract | Medical imaging, such as chest X-rays, gives an acceptable image of lung functions. Manipulating these images by a radiologist is difficult, thus delaying the diagnosis. Coronavirus is a disease that affects the lung area. Lung segmentation has a significant function in assessing lung disorders. The process of segmentation has seen widespread use of deep learning algorithms. The U-Net is one of the most significant semantic segmentation frameworks for a convolutional neural network. In this paper, the proposed U-Net architecture is evaluated on 565 datasets divided into 500 training images and 65 validation images, For chest X-ray. The findings of the experiments demonstrate that the suggested strategy successfully achieved competitive outcomes with 91.47% and 89.18% accuracy, 0.7494 and 0.7480 IoU, 19.23% and 26.11% loss for training and validation images, respectively. | en |
| dc.format | text | cs |
| dc.format.extent | 49-53 | cs |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Mendel. 2022 vol. 28, č. 2, s. 49-53. ISSN 1803-3814 | cs |
| dc.identifier.doi | 10.13164/mendel.2022.2.049 | en |
| dc.identifier.issn | 2571-3701 | |
| dc.identifier.issn | 1803-3814 | |
| dc.identifier.uri | http://hdl.handle.net/11012/208747 | |
| dc.language.iso | en | cs |
| dc.publisher | Institute of Automation and Computer Science, Brno University of Technology | cs |
| dc.relation.ispartof | Mendel | cs |
| dc.relation.uri | https://mendel-journal.org/index.php/mendel/article/view/192 | cs |
| dc.rights | Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license | en |
| dc.rights.access | openAccess | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0 | en |
| dc.subject | U-Net | en |
| dc.subject | Segmentation | en |
| dc.subject | Deep learning | en |
| dc.subject | Coronavirus | en |
| dc.subject | lung | en |
| dc.subject | X-ray | en |
| dc.subject | CNN | en |
| dc.title | Segmentation of Chest X-Ray Images Using U-Net Model | en |
| dc.type.driver | article | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
| eprints.affiliatedInstitution.faculty | Fakulta strojního inženýrství | cs |
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