Multi-scale feature pyramid fusion network for medical image segmentation

被引:0
作者
Bing Zhang
Yang Wang
Caifu Ding
Ziqing Deng
Linwei Li
Zesheng Qin
Zhao Ding
Lifeng Bian
Chen Yang
机构
[1] Guizhou University,Power Systems Engineering Research Center, Ministry of Education, College of Big Data and Information Engineering
[2] Fudan University,Frontier Institute of Chip and System
来源
International Journal of Computer Assisted Radiology and Surgery | 2023年 / 18卷
关键词
Medical image segmentation; Multi-Scale attention module; Stacked feature pyramid module; Feature perception module;
D O I
暂无
中图分类号
学科分类号
摘要
引用
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页码:353 / 365
页数:12
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[1]  
Frid-Adar M(2018)GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification Neurocomputing 321 7-3320
[2]  
Diamant I(2020)HIFUNet: multi-class segmentation of uterine regions from MR images using global convolutional networks for HIFU surgery planning IEEE Trans Med Imaging 39 3309-122825
[3]  
Klang E(2020)Skin lesion segmentation based on multi-scale attention convolutional neural network IEEE Access 8 122811-207833
[4]  
Amitai M(2020)Automated maxillofacial segmentation in panoramic dental x-ray images using an efficient encoder-decoder network IEEE Access 8 207822-18533
[5]  
Goldberger J(2017)Nuclear architecture analysis of prostate cancer via convolutional neural networks[J] IEEE Access 5 18526-585
[6]  
Greenspan H(2020)Diabetic retinopathy diagnosis using multichannel generative adversarial network with semisupervision IEEE Trans Autom Sci Eng 18 574-78
[7]  
Zhang C(2017)Lung cancer detection and classification with 3D convolutional neural network (3D-CNN) Lung Cancer 8 409-996
[8]  
Shu H(2017)Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation Med Image Anal 36 61-14
[9]  
Yang G(2019)Stacked bidirectional convolutional LSTMs for deriving 3D non-contrast ct from spatiotemporal 4D CT IEEE Trans Med Imaging 39 985-51569
[10]  
Li F(2021)Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models Sci Rep 11 1-672