Biotibbiy tasvirlarini segmentatsiya qilishda gibrid neyron tarmoq modellari
Biotibbiy tasvirlarini segmentatsiya qilishda gibrid neyron tarmoq modellari
Keywords:
Biotibbiy tasvirlarini segmentatsiya qilishda gibrid neyronAbstract
Biotibbiy tasvirlarni segmentatsiya qilish uchun U-Mamba gibrid arxitekturasi taklif qilindi. Ushbu gibrid arxitekturani yaratish uchun Konvolyutsion neyron tarmoqlarni (CNN) va Kosmik ketma-ket modellari (SSM) bilan birlashtiradi. Bu yondashuv mahalliy xususiyatlarni olishda CNN-ning kuchli tomonlarini SSM-larning tasvirlardagi uzoq masofali bog‗liqliklarni olish qobiliyatini birlashtiradi. Ushbu usul, U-Mamba, 3D, hamda 2D biotibbiy tasvirlarni segmentlash uchun mos bo‗lgan ko‗p qirrali tarmoq sifatida ishlab chiqilgan. U-Mamba o‗z-o‗zini sozlash xususiyatini taqdim etadi, bu unga turli xil ma'lumotlar to‗plamlariga osongina moslashishga imkon beradi va shu bilan uning kengaytirilishi va moslashuvchanligini oshiradi.[1]
References
Jun Ma, Feifei Li, Bo Wang, U-Mamba: Enhancing Long Mamba: Enhancing Long Mamba: Enhancing LongMamba: Enhancing LongMamba: Enhancing Long Mamba: Enhancing LongMamba: Enhancing LongMamba: Enhancing Long Mamba: Enhancing Long-range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image range Dependency for Biomedical Image SegmentationSegmentationSegmentationSegmentation Segmentation Segmentation https://doi.org/10.48550/arXiv.2401.04722 , https://wanglab.ai/u-mamba.html.
Ayyuce Demirbas. U-Mamba: A Novel Approach to Biomedical Image Segmentation. Feb 4,2024. http://arxiv.org/abs/2401.04722 3.Ziyang Wang, Jian-Qing Zheng, Yichi Zhang, Ge Cui, Lei Li, Mamba -UNet: UNet UNet: UNetUNet: UNet UNet: UNetUNet: UNet UNet: UNetUNet: UNet-Like Pure Visual Like Pure Visual Like Pure Visual Like Pure Visual Like Pure Visual Like Pure Visual Like Pure Visual Like Pure Visual Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/Mamba for Medical Image Segmentation https://doi.org/10.48550/ Mamba for Medical Image Segmentation https://doi.org/10.48550/ arXiv.2402.05079 arXiv.2402.05079 arXiv.2402.05079
Кутненко О.А., Плясунов А.В. NP - трудность некоторой задачи цензурирования данных // Дискретн. анализ и исслед. опер. 2021. Т. 28. Вып. 2. С. 60–73.
Борисова И.А., Кутненко О.А. Исправление диагностических ошибок в целевом признаке с помощью функции конкурентного сходства // Математическая биология и биоинформатика. 2018. № 1. С. 38–49.
