D2A U-Net: Automatic segmentation of COVID-19 CT slices based on dual attention and hybrid dilated convolution
Tài liệu tham khảo
Wang, 2020, A novel coronavirus outbreak of global health concern, Lancet, 395, 470, 10.1016/S0140-6736(20)30185-9
2020
Wang, 2020, Detection of sars-cov-2 in different types of clinical specimens, Jama, 323, 1843
2020
Lei, 2020, Ct imaging of the 2019 novel coronavirus (2019-ncov) pneumonia, Radiology, 295, 18, 10.1148/radiol.2020200236
Ng, 2020, Imaging profile of the covid-19 infection: radiologic findings and literature review, Radiology: Cardiothoracic Imaging, 2
Pan, 2020, 200370
Wang, 2020
Zhou, 2020
Fan, 2020, Inf-net: automatic covid-19 lung infection segmentation from ct images, IEEE Trans. Med. Imag., 10.1109/TMI.2020.2996645
Zheng, 2020
Ouyang, 2020, Dual-sampling attention network for diagnosis of covid-19 from community acquired pneumonia, IEEE Trans. Med. Imag., 10.1109/TMI.2020.2995508
Kamble, 2020, A review on lung and nodule segmentation techniques, 555
Mansoor, 2014, A generic approach to pathological lung segmentation, IEEE Trans. Med. Imag., 33, 2293, 10.1109/TMI.2014.2337057
Yao, 2011, Computer-aided diagnosis of pulmonary infections using texture analysis and support vector machine classification, Acad. Radiol., 18, 306, 10.1016/j.acra.2010.11.013
Shaziya, 2018, Automatic lung segmentation on thoracic ct scans using u-net convolutional network
Zhao, 2018, Lung segmentation in ct images using a fully convolutional neural network with multi-instance and conditional adversary loss, 505
Corbetta, 2002, Control of goal-directed and stimulus-driven attention in the brain, Nat. Rev. Neurosci., 3, 201, 10.1038/nrn755
Mnih, 2014, Recurrent models of visual attention, 2204
Hu, 2018, Squeeze-and-excitation networks, 7132
Woo, 2018, Cbam: convolutional block attention module, 3
Wang, 2017, Residual attention network for image classification, 3156
Li, 2018
Fisher, 2015
Wang, 2018, Smoothed dilated convolutions for improved dense prediction, 2486
Mehta, 2018, Espnet: efficient spatial pyramid of dilated convolutions for semantic segmentation, 552
Park, 2018
Wang, 2018, Understanding convolution for semantic segmentation, 1451
Xie, 2020, Relational modeling for robust and efficient pulmonary lobe segmentation in ct scans, IEEE Trans. Med. Imag., 39, 2664, 10.1109/TMI.2020.2995108
Wang, 2020, A noise-robust framework for automatic segmentation of covid-19 pneumonia lesions from ct images, IEEE Trans. Med. Imag., 39, 2653, 10.1109/TMI.2020.3000314
Chen, 2020
Zhou, 2020, A rapid, accurate and machine-agnostic segmentation and quantification method for ct-based covid-19 diagnosis, IEEE Trans. Med. Imag., 39, 2638, 10.1109/TMI.2020.3001810
Qiu, 2020
Ronneberger, 2015, U-net: convolutional networks for biomedical image segmentation, 234
Xie, 2017, Aggregated residual transformations for deep neural networks, 1492
Oktay, 2018
Ma, 2020
Zhou, 2018, Unet++: a nested u-net architecture for medical image segmentation, 3
Long, 2015, Fully convolutional networks for semantic segmentation, 3431
Chen, 2017
Wang, 2021, Does non-covid-19 lung lesion help? investigating transferability in covid-19 ct image segmentation, Comput. Methods Progr. Biomed., 202, 106004, 10.1016/j.cmpb.2021.106004
Yan, 2020
Ma, 2021, Toward data-efficient learning: a benchmark for covid-19 ct lung and infection segmentation, Med. Phys., 48, 1197, 10.1002/mp.14676