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Peiqing Lv

Showing results (1-10 of 7) with videos related to

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Scientific Reports|October 10, 2022
Deep supervision and atrous inception-based U-Net combining CRF for automatic liver segmentation from CTPeiqing Lv, Jinke Wang, Xiangyang Zhang, et al.
Computer Methods and Programs in Biomedicine|July 18, 2021
SAR-U-Net: Squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed TomographyJinke Wang, Peiqing Lv, Haiying Wang, et al.
Computational and Mathematical Methods in Medicine|August 23, 2021
SERR-U-Net: Squeeze-and-Excitation Residual and Recurrent Block-Based U-Net for Automatic Vessel Segmentation in Retinal ImageJinke Wang, Xiang Li, Peiqing Lv, et al.
Journal of Digital Imaging|June 17, 2022
Automatic Liver Segmentation Using EfficientNet and Attention-Based Residual U-Net in CTJinke Wang, Xiangyang Zhang, Peiqing Lv, et al.
Mathematical Biosciences and Engineering : MBE|February 9, 2022
An improved residual U-Net with morphological-based loss function for automatic liver segmentation in computed tomographyPeiqing Lv, Jinke Wang, Xiangyang Zhang, et al.
Mathematical Biosciences and Engineering : MBE|April 18, 2022
Residual based attention-Unet combing DAC and RMP modules for automatic liver tumor segmentation in CTRongrong Bi, Chunlei Ji, Zhipeng Yang, et al.
IEEE Transactions on Medical Imaging|October 13, 2025
CiSeg: Unsupervised Cross-Modality Adaptation for 3D Medical Image Segmentation via Causal InterventionPeiqing Lv, Yaonan Wang, Min Liu, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Scientific Reports|October 10, 2022
Deep supervision and atrous inception-based U-Net combining CRF for automatic liver segmentation from CTPeiqing Lv, Jinke Wang, Xiangyang Zhang, et al.
Computer Methods and Programs in Biomedicine|July 18, 2021
SAR-U-Net: Squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed TomographyJinke Wang, Peiqing Lv, Haiying Wang, et al.
Computational and Mathematical Methods in Medicine|August 23, 2021
SERR-U-Net: Squeeze-and-Excitation Residual and Recurrent Block-Based U-Net for Automatic Vessel Segmentation in Retinal ImageJinke Wang, Xiang Li, Peiqing Lv, et al.
Journal of Digital Imaging|June 17, 2022
Automatic Liver Segmentation Using EfficientNet and Attention-Based Residual U-Net in CTJinke Wang, Xiangyang Zhang, Peiqing Lv, et al.
Mathematical Biosciences and Engineering : MBE|February 9, 2022
An improved residual U-Net with morphological-based loss function for automatic liver segmentation in computed tomographyPeiqing Lv, Jinke Wang, Xiangyang Zhang, et al.
Mathematical Biosciences and Engineering : MBE|April 18, 2022
Residual based attention-Unet combing DAC and RMP modules for automatic liver tumor segmentation in CTRongrong Bi, Chunlei Ji, Zhipeng Yang, et al.
IEEE Transactions on Medical Imaging|October 13, 2025
CiSeg: Unsupervised Cross-Modality Adaptation for 3D Medical Image Segmentation via Causal InterventionPeiqing Lv, Yaonan Wang, Min Liu, et al.
Pageof 1