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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/56938
Title: Generative adversarial network for medical image segmentation
Authors: Zhao Di
Tang Yi
Keywords: материалы конференций;segmentation method;medical image;medical image segmentation
Issue Date: 2024
Publisher: БГУИР
Citation: Zhao Di. Generative adversarial network for medical image segmentation / Zhao Di, Tang Yi // Информационные технологии и управление : материалы 60-ой научной конференции аспирантов, магистрантов и студентов, Минск, 22–26 апреля 2024 года / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: Л. Ю. Шилин [и др.]. – Минск, 2024. – С. 44.
Abstract: In this paper, a U-Net medical image segmentation method based on generative adversarial networks is proposed. This method is used to solve the problem of performance degradation of modeling algorithms due to insufficient training samples in medical image segmentation.
URI: https://libeldoc.bsuir.by/handle/123456789/56938
Appears in Collections:Информационные технологии и управление : материалы 60-й научной конференции аспирантов, магистрантов и студентов (2024)

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