Comparison of Shallow and Deep Learning Methods on Classifying the Regional Pattern of Diffuse Lung Disease-Reference-Cited by-同舟云学术

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Comparison of Shallow and Deep Learning Methods on Classifying the Regional Pattern of Diffuse Lung Disease

Published:2017-10-17 Issue:4 Volume:31 Page:415-424
ISSN:0897-1889
Container-title:Journal of Digital Imaging
language:en
Short-container-title:J Digit Imaging

Author:

Kim Guk Bae,Jung Kyu-Hwan,Lee Yeha,Kim Hyun-Jun,Kim Namkug^ORCID,Jun Sanghoon,Seo Joon Beom,Lynch David A.

Funder

Ministry of Trade, Industry and Energy

MSIP/IITP

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://link.springer.com/article/10.1007/s10278-017-0028-9/fulltext.html

Reference30 articles.

1. Raghu G et al.: Incidence and prevalence of idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 174(7):810–816, 2006

2. Scatarige JC et al.: Utility of high-resolution CT for management of diffuse lung disease: Results of a survey of US pulmonary physicians. Acad Radiol 10(2):167–175, 2003

3. Grenier P et al.: Chronic diffuse interstitial lung disease: Diagnostic value of chest radiography and high-resolution CT. Radiology 179(1):123–132, 1991

4. Kalender WA et al.: Measurement of pulmonary parenchymal attenuation: Use of spirometric gating with quantitative CT. Radiology 175(1):265–268, 1990

5. Chabat F, Yang G-Z, Hansell DM: Obstructive lung diseases: Texture classification for differentiation at CT 1. Radiology 228(3):871–877, 2003

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