Residual Attention Network for distinction between visible optic disc drusen and healthy optic discs
Artykuł w czasopiśmie
MNiSW
140
Lista 2024
| Status: | |
| Autorzy: | Nowomiejska Katarzyna, Powroźnik Paweł, Skublewska-Paszkowska Maria, Adamczyk Katarzyna, Concilio Marina, Sereikaite Liveta, Zemaitiene Reda, Toro Mario Damiano, Rejdak Robert |
| Dyscypliny: | |
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| Rok wydania: | 2024 |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Wolumen/Tom: | 176 |
| Numer artykułu: | 108056 |
| Strony: | 1 - 12 |
| Web of Science® Times Cited: | 0 |
| Scopus® Cytowania: | 0 |
| Bazy: | Web of Science | Scopus |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | TAK |
| Licencja: | |
| Sposób udostępnienia: | Witryna wydawcy |
| Wersja tekstu: | Ostateczna wersja opublikowana |
| Czas opublikowania: | W momencie opublikowania |
| Data opublikowania w OA: | 28 stycznia 2024 |
| Abstrakty: | angielski |
| In this study the authors propose a new solution for distinguish healthy cases and those with optic disc drusen (ODD) utilizing Residual Attention Network (RAN). This network architecture, which employs convolutional layers, integrates a diverse attention mechanism within its deep structure. In this study, an unique approach is adopted, involving the iterative division and subsequent recombination of a single image B-scan obtained using OCT-A. Overall, 116 images of ODD obtained using optical coherence tomography - angiography (OCT-A) have been analysed and compared to images of healthy optic discs. A sequence of trials was conducted, considering the random partitioning of data into training, validation, and test elements, with proportions of 60 %, 20 %, and 20 %, respectively. The minimum accuracy exceeded 86 %, while the maximum values were higher than 98 %. The accuracy for analyzing healthy cases and ones with ODD has gained very satisfactory results. Our study shows that RAN is a suitable tool for distinguishing between optic disc drusen and normal optic discs on the basis of OCT-A B-scans of the optic nerve head. Deep learning may be used as a possible solution to screen for patients with ODD. |
