Diagnostic of Cystic Fibrosis in Lung Computer Tomographic Images using Image Annotation and Improved PSPNet Modelling
| Parent link: | Journal of Physics: Conference Series Vol. 1611 : Prospects of Fundamental Sciences Development (PFSD-2020).— 2020.— [012062, 6 p.] |
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| Autor Corporativo: | |
| Outros autores: | , , , , , |
| Summary: | Title screen The research deals with the development of an algorithm for detecting pathological formation in cystic fibrosis using the PSPNet model with focal loss. The model allows data sets to be entered in accordance to their similarities based on their pathological diagnostic signs. The simple and effective algorithm structure groups annotated images, processes them in a multiscale CNN, and localizes areas of cystic fibrosis in the lungs with high accuracy. |
| Publicado: |
2020
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| Subjects: | |
| Acceso en liña: | https://doi.org/10.1088/1742-6596/1611/1/012062 http://earchive.tpu.ru/handle/11683/63235 |
| Formato: | Electrónico Capítulo de libro |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=662793 |
| Summary: | Title screen The research deals with the development of an algorithm for detecting pathological formation in cystic fibrosis using the PSPNet model with focal loss. The model allows data sets to be entered in accordance to their similarities based on their pathological diagnostic signs. The simple and effective algorithm structure groups annotated images, processes them in a multiscale CNN, and localizes areas of cystic fibrosis in the lungs with high accuracy. |
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| DOI: | 10.1088/1742-6596/1611/1/012062 |