| DC Field | Value | Language |
|---|
| dc.contributor.author | Zhao Di | - |
| dc.contributor.author | Gourinovitch, A. B. | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2025-01-13T07:19:25Z | - |
| dc.date.available | 2025-01-13T07:19:25Z | - |
| dc.date.issued | 2024 | - |
| dc.identifier.citation | Zhao Di. Transformer-based denoising method for medical images / Zhao Di, A. B. Gourinovitch // Информационные технологии и системы 2024 (ИТС 2024) = Information Technologies and Systems 2024 (ITS 2024) : материалы международной научной конференции, Минск, 20 ноября 2024 г. / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: Л. Ю. Шилин [и др.]. – Минск, 2024. – С. 194-195. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/58700 | - |
| dc.description.abstract | Biomedical image segmentation is essential for accurate disease diagnosis. However, issues like noise and artifacts
in medical images can hinder effective diagnosis. This paper presents a Transformer-based method for medical image segmentation denoising, which uses self-attention to remove noise and retain image details, thus enhancing diagnostic accuracy. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | БГУИР | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | information technology | en_US |
| dc.subject | medicine | en_US |
| dc.subject | noise reduction | en_US |
| dc.subject | transformer method | en_US |
| dc.subject | diagnostics | en_US |
| dc.title | Transformer-based denoising method for medical images | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | ИТС 2024
|
