参考文献/References:
[1] AL-SHARIFY Z T,AL-SHARIFY T A,AL-SHARIFY N T,et al.A critical review on medical imaging techniques(CT and PET scans)in the medical field[J].IOP Conference Series:Materials Science and Engineering,2020,870:012043.DOI:10.1088/1757-899X/870/1/012043.
[2] BERG W A,GUR D,BANDOS A I,et al.Impact of original and artificially improved artificial intelligence-based computer-aided diagnosis on breast US interpretation[J].Journal of Breast Imaging,2021,3(3):301-311.DOI:10.1093/jbi/wbab013.
[3] PADMANABAN S,THIRUNENKADAM K,PADMAPRIYA S T,et al.A role of medical imaging techniques in human brain tumor treatment[J].International Journal of Recent Technology and Engineering,2019,8(4S2):565-568.DOI:10.35940/ijrte.D1105.1284S219.
[4] 张继武,张道兵,史舒娟,等.基于水平集方法的数字胸片图像分割[J].中国图象图形学报,2004,9(12):65-71.DOI:10.3969/j.issn.1006-8961.2004.12.009.
[5] CANDEMIR S,JAEGER S,PALANIAPPAN K,et al.Graph cut based automatic lung boundary detection in chest radiographs[C]//1st Annual IEEE Healthcare Innovation Conference.Houston:IEEE Press,2012:31-34.
[6] 佘广南,陈莹胤,钟丽明,等.基于密集特征匹配的胸片肺野自动分割[J].南方医科大学学报,2016,36(1):61-66.DOI:10.3969/j.issn.1673-4254.2016.01.11.
[7] MATSUYAMA E.A novel method for automated lung region segmentation in chest X-ray images[J].Journal of Biomedical Science and Engineering,2021,14(6):288-299.DOI:10.4236/jbise.2021.146024.
[8] 秦子亮,李朝锋.基于卷积神经网络的胸片肺野自动分割[J].传感器与微系统,2017,36(10):64-66,69.DOI:10.13873/J.1000-9787(2017)10-0064-03.
[9] KIM M,LEE B D.Automatic lung segmentation on chest X-rays using self-attention deep neural network[J].Sensors,2021,21(2):369.DOI:10.3390/S21020369.
[10] RONNEBERGER O,FISCHER P,BROX T.U-net: Convolutional networks for biomedical image segmentation[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention.Munich:Springer,2015:234-241.
[11] SINGH A,LALL B,PANIGRAHI B K,et al.Deep LF-Net: Semantic lung segmentation from Indian chest radiographs including severely unhealthy images[J].Biomedical Signal Processing and Control,2021,68:102666.DOI:10.1016/J.BSPC.2021.102666.
[12] ABID I,ALMAKDI S,RAHMAN H,et al.A convolutional neural network for skin lesion segmentation using double U-net architecture[J].Intelligent Automation and Soft Computing,2022,33(3):1407-1421.DOI:10.32604/IASC.2022.023753.
[13] LI Meiyu,LIAN Fenghui,LI Yang,et al.Attention-guided duplex adversarial U-net for pancreatic segmentation from computed tomography images[J].Journal of Applied Clinical Medical Physics,2022,23(4):e13537.DOI:10.1002/ACM2.13537.
[14] HUSSAIN S,GUO Fan,LI Weiqing,et al.DilUnet: A U-net based architecture for blood vessels segmentation[J].Computer Methods and Programs in Biomedicine,2022,218:106732.DOI:10.1016/J.CMPB.2022.106732.
[15] PANAHI A,ASKARI M R,AKRAMI M,et al.Deep residual neural network for COVID-19 detection from chest X-ray images[J].SN Computer Science,2022,3(2):1-10.DOI:10.1007/S42979-022-01067-3.
[16] DU Getao,ZHAN Yonghua,ZHANG Yue,et al.Automated segmentation of the gastrocnemius and soleus in shank ultrasound images through deep residual neural network[J].Biomedical Signal Processing and Control,2022,73:103447.DOI:10.1016/J.BSPC.2021.103447.
[17] CHEN Kuanbing,XUAN Ying,LIN Aijun,et al.Lung computed tomography image segmentation based on U-net network fused with dilated convolution[J].Computer Methods and Programs in Biomedicine,2021,207:106170.DOI:10.1016/J.CMPB.2021.106170.
[18] SZEGEDY C,VANHOUCKE V,IOFFE S,et al.Rethinking the inception architecture for computer vision[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Las Vegas:IEEE Press,2016:2818-2826.DOI:10.1109/CVPR.2016.308.
[19] CHENG Dachuan,LIU C C,HSIEH T C,et al.Bone metastasis detection in the chest and pelvis from a whole-body bone scan using deep learning and a small dataset[J].Electronics,2021,10(10):1201.DOI:10.3390/ELECTRONICS10101201.
[20] SHORTEN C,KHOSHGOFTAAR T M.A survey on image data augmentation for deep learning[J].Journal of Big Data,2019,6(1):1-48.DOI:10.1186/s40537-019-0197-0.
[21] NALEPA J,MARCINKIEWICZ M,KAWULOK M.Data augmentation for brain-tumor segmentation: A review[J].Frontiers in Computational Neuroscience,2019,13:83.DOI:10.3389/fncom.2019.00083.
[22] WANG Xiang,WANG Kai,LIAN Shiguo.A survey on face data augmentation for the training of deep neural networks[J].Neural Computing and Applications,2020,32(19):15503-15531.DOI:10.1007/s00521-020-04748-3.
[23] DUONG H T,NGUYEN T T A.A review: Preprocessing techniques and data augmentation for sentiment analysis[J].Computational Social Networks,2021,8(1):1-16.DOI:10.1186/S40649-020-00080-X.
[24] SHAMBHU S,KOUNDAL D,DAS P.Binary classification of COVID-19 CT images using CNN: COVID diagnosis using CT[J].International Journal of E-Health and Medical Communications,2021,13(2):1-13.DOI:10.4018/IJEHMC.20220701.OA4.
[25] SUN Shuhan,DUAN Lizhen,XU Zhiyong,et al.Blind deblurring based on sigmoid function[J].Sensors,2021,21(10):3484.DOI:10.3390/S21103484.