A deep convolutional neural network architecture for interstitial lung disease pattern classification-Reference-Cited by-同舟云学术

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A deep convolutional neural network architecture for interstitial lung disease pattern classification

Published:2020-01-22 Issue:4 Volume:58 Page:725-737
ISSN:0140-0118
Container-title:Medical & Biological Engineering & Computing
language:en
Short-container-title:Med Biol Eng Comput

Author:

Huang Sheng,Lee Feifei,Miao Ran,Si Qin,Lu Chaowen,Chen Qiu

Funder

The Program for Professor of Special Appointment

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Biomedical Engineering

Link

http://link.springer.com/content/pdf/10.1007/s11517-019-02111-w.pdf

Reference43 articles.

1. Altaf F, Islam S, Akhtar N, Janjua NK (2019) Going deep in medical image analysis: Concepts, methods, challenges and future directions. arXiv:1902.05655

2. Anthimopoulos M, Christodoulidis S, Ebner L, Christe A, Mougiakakou S (2016) Lung pattern classification for interstitial lung diseases using a deep convolutional neural network. IEEE Trans Med Imag 35 (5):1207–1216

3. Aziz ZA, Wells AU, Hansell DM, Bain G, Copley SJ, Desai SR, Ellis SM, Gleeson FV, Grubnic S, Nicholson AG, et al. (2004) Hrct diagnosis of diffuse parenchymal lung disease: inter-observer variation. Thorax 59(6):506–511

4. Azizpour H, Razavian AS, Sullivan J, Maki A, Carlsson S (2016) Factors of transferability for a generic ConvNet representation. IEEE Trans Pattern Anal Mach Intell 38(9):1790–1802

5. Chen G, Zhang J, Zhuo D, Pan Y, Pang C (2019) Identification of pulmonary nodules via CT images with hierarchical fully convolutional networks. Medical & Biological Engineering & Computing:1–14

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