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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/58700
Title: Transformer-based denoising method for medical images
Authors: Zhao Di
Gourinovitch, A. B.
Keywords: материалы конференций;information technology;medicine;noise reduction;transformer method;diagnostics
Issue Date: 2024
Publisher: БГУИР
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.
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.
URI: https://libeldoc.bsuir.by/handle/123456789/58700
Appears in Collections:ИТС 2024

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