[1] 余浩松, 邹永宁, 张智斌. 利用CAD模型的不完全扫描CT图像重建. 光学学报, 41, 107-117(2021).

     H S YU, Y N ZOU, ZH B ZHANG et al. Image reconstruction of incomplete CT scanning using a CAD model. Acta Optica Sinica, 41, 107-117(2021).

[2] 章斌, 卢洪义, 刘舜. 发动机部件CT图像特征提取与区域生长算法. 兵工学报, 44, 1171-1180(2023).

     B ZHANG, H Y LU, SH LIU et al. Feature extraction and region growing algorithm for processing CT scans of engine parts. Acta Armamentarii, 44, 1171-1180(2023).

[3] X K YU, Z W WANG, Y H WANG et al. Edge detection of agricultural products based on morphologically improved canny algorithm. Mathematical Problems in Engineering, 2021, 6664970(2021).

[4] L ZOU, L T SONG, T WEISE et al. A survey on regional level set image segmentation models based on the energy functional similarity measure. Neurocomputing, 452, 606-622(2021).

[5] H Q LIU, F ZHAO. Multiobjective fuzzy clustering with multiple spatial information for Noisy color image segmentation. Applied Intelligence, 51, 5280-5298(2021).

[6] M LIASKOS, M A SAVELONAS, P A ASVESTAS et al. Vertebrae， IVD and spinal canal boundary extraction on MRI， utilizing CT-trained active shape models. International Journal of Computer Assisted Radiology and Surgery, 16, 2201-2214(2021).

[7] CH J LIU, L ZENG. Industrial Computerized Tomography image segmentation based on two Cellular Neural Networks. Computer Engineering and Applications, 44, 206-208(2008).

     刘长江, 曾理. 基于两组细胞神经网络的工业CT图像分割. 计算机工程与应用, 44, 206-208(2008).

[8] E X ZHAO, Y Y HE, K SHEN et al. Casting CT image segmentation algorithm based on deep learning. Chinese Journal of Scientific Instrument, 44, 176-184(2023).

     赵恩玄, 何云勇, 沈宽. 基于深度学习的铸件CT图像分割算法. 仪器仪表学报, 44, 176-184(2023).

[9] C BEECHE, J P SINGH, J K LEADER et al. Super U-Net： a modularized generalizable architecture. Pattern Recognition, 128, 108669(2022).

[10] H HAN, C Q GAO, Y ZHAO et al. Polycrystalline silicon wafer defect segmentation based on deep convolutional neural networks. Pattern Recognition Letters, 130, 234-241(2020).

[11] N B DEVI, A C KAVIDA, R MURUGAN. Feature extraction and object detection using fast-convolutional neural network for remote sensing satellite image. Journal of the Indian Society of Remote Sensing, 50, 961-973(2022).

[12] 王一, 龚肖杰, 苏皓. 基于改进U-net的金属工件表面缺陷图像分割方法. 应用光学, 44, 86-92(2023).

     Y WANG, X J GONG, H SU. Image segmentation method of surface defects for metal workpieces based on improved U-net. Journal of Applied Optics, 44, 86-92(2023).

[13] J GOU, X Y WU, L LIU. Detection and segmentation of defects in industrial CT images based on mask R-CNN. Journal of Computers, 31, 141-154(2020).

[14] W YUAN, J WANG, W B XU. Shift pooling PSPNet： rethinking PSPNet for building extraction in remote sensing images from entire local feature pooling. Remote Sensing, 14, 4889(2022).

[15] Z J NIU, W LIU, J Y ZHAO et al. DeepLab-based spatial feature extraction for hyperspectral image classification. IEEE Geoscience and Remote Sensing Letters, 16, 251-255(2019).

[16] C Q YU, B XIAO, C X GAO et al. Lite-HRNet： a lightweight high-resolution network, 20, 10435-10445(2021).

[17] L C CHEN, G PAPANDREOU, I KOKKINOS et al. DeepLab： semantic image segmentation with deep convolutional nets， atrous convolution， and fully connected CRFs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 834-848(2018).

[18] Q Q NING, J K ZHU, C CHEN. Very fast semantic image segmentation using hierarchical dilation and feature refining. Cognitive Computation, 10, 62-72(2018).

[19] Y BAI, J LI, L J SHI et al. DME-DeepLabV³⁺： a lightweight model for diabetic macular edema extraction based on DeepLabV³⁺ architecture. Frontiers in Medicine, 10, 1150295(2023).

[20] 龙超, 金恒, 黎玲. 基于特征融合的非局部均值CT图像降噪. 光学学报, 42, 1134024(2022).

     CH LONG, H JIN, L LI et al. CT image denoising with non-local means based on feature fusion. Acta Optica Sinica, 42, 1134024(2022).