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|a Chest X-ray image segmentation method based on a dilated multiscale U-Net
|f Wang Yuqian, Li Qilun
|g Science supervisor Aksyonov S. V.
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| 320 |
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|a References: 7 tit
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| 330 |
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|a This paper proposes a dilated multiscale U-Net for chest X ray image segmentation. By fusing multi scale contextual information and channel features via dilated convolutions and an improved inception module, the method enhances lesion detection and localization. Experiments on the ChestX ray14 subset demonstrate superior accuracy and efficiency
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| 336 |
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|a Текстовый файл
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1 |
|0 687244
|9 687244
|t Молодежь и современные информационные технологии
|o сборник трудов XXIII Международной научно-практической конференции студентов, аспирантов и молодых ученых, 18–20 февраля 2026 г., Томск
|c Томск
|d 2026
|n Изд-во ТПУ
|u conference_tpu-2026-C04.pdf
|v С. 284-287
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| 545 |
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|a Компьютерное зрение
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|a электронный ресурс
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|a труды учёных ТПУ
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|a image segmentation
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| 610 |
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|a deep learning
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|a U-Ne
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|a multi-scale features
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| 610 |
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|a dilated convolution
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| 610 |
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|a chest radiography
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| 610 |
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|a сегментация изображений
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| 610 |
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|a глубокое обучение
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| 610 |
1 |
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|a многомасштабные функции
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| 610 |
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|a рентгенография
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|a Wang Yuqian
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|a Li Qilun
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|a Aksyonov
|b S. V.
|4 727
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|b 63413507
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|u https://earchive.tpu.ru/handle/11683/139098
|z https://earchive.tpu.ru/handle/11683/139098
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| 942 |
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|c CF
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