Funder
National Natural Science Foundation of China
Xiamen Science and Technology Plan Project
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Reference34 articles.
1. Black RE, Cousens S, Johnson HL et al (2010) Global, regional, and national causes of child mortality in 2008: a systematic analysis. Lancet 375:1969–1987
2. Zhao B, Guo Y, Zheng C et al (2019) Using deep-learning techniques for pulmonary-thoracic segmentations and improvement of pneumonia diagnosis in pediatric chest radiographs. Pediatr Pulmonol 54:1617–1626
3. Hwang S, Park S (2017) Accurate lung segmentation via network-wise training of convolutional networks. Deep Learning in Medical lmage Analysis and Multimodal learning for Clinical Decision Support. Springer, pp 92–99
4. Mansoor A, Cerrolaza JJ, Perez G et al (2019) A generic approach to lung field segmentation from chest radiographs using deep space and shape learning. IEEE Trans Biomed Eng 67:1206–1220
5. Garin M, Carballo DF, Montet R (2012) High discordance of chest x-ray and CT for detection of pulmonary opacities in ED patients: implications for diagnosing pneumonia. Am J Respir Crit Care Med 31:10.1164