scholarly journals A Generic Approach to Lung Field Segmentation From Chest Radiographs Using Deep Space and Shape Learning

2020 ◽  
Vol 67 (4) ◽  
pp. 1206-1220 ◽  
Author(s):  
Awais Mansoor ◽  
Juan J. Cerrolaza ◽  
Geovanny Perez ◽  
Elijah Biggs ◽  
Kazunori Okada ◽  
...  
2018 ◽  
Vol 22 (3) ◽  
pp. 842-851 ◽  
Author(s):  
Wei Yang ◽  
Yunbi Liu ◽  
Liyan Lin ◽  
Zhaoqiang Yun ◽  
Zhentai Lu ◽  
...  

2016 ◽  
Vol 6 (2) ◽  
pp. 338-348 ◽  
Author(s):  
Xuechen Li ◽  
Suhuai Luo ◽  
Qingmao Hu ◽  
Jiaming Li ◽  
Dadong Wang ◽  
...  

2012 ◽  
Vol 433-440 ◽  
pp. 3564-3569
Author(s):  
Jun Lai ◽  
Ke Xu

Conventional methods that perform lung segment -ation in CT slices rely on a large contrast in hounsfield units between the lung and surrounding tissues. However, the lung fields are affected by high density pathologies, and they are discontinuities in the pixel intensities, the traditional segment- ation methods can’t get the good results. Here, we present a new segmentation method of the active contour, which is constraining with respect to a set of fixed reference shapes of lung fields. This approach is based on the shapes descriptors by the legendre moments computed from the shape regions, and it can be used in some complex lung field segmentation, especially suitable for the segmentation of lung field with the juxta-pleural pulmonary nodules. Experiments illustrate that the proposed method is able to segment the lung fields in the CT images successfully.


2014 ◽  
Vol 33 (9) ◽  
pp. 1761-1780 ◽  
Author(s):  
Yeqin Shao ◽  
Yaozong Gao ◽  
Yanrong Guo ◽  
Yonghong Shi ◽  
Xin Yang ◽  
...  

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