Segmentation of Chest Radiographs for Tuberculosis Screening Using Kernel Mapping and Graph Cuts

Author:

Fatima Ayesha,Tariq Anam,Akhtar Mahmood,Zahid Hira

Publisher

Springer International Publishing

Reference21 articles.

1. Arbabshirani, M. R., Dallal, A. H., Agarwal, C., Patel, A., & Moore, G. (2017). Accurate segmentation of lung fields on chest radiographs using deep convolutional networks. In SPIE Medical Imaging (pp. 1013305–1013305). International Society for Optics and Photonics.

2. Candemir, S., Jaeger, S., Palaniappan, K., Antani, S., & Thoma, G. (2012). Graph-cut based automatic lung boundary detection in chest radiographs. In IEEE Healthcare Technology Conference: Translational Engineering in Health & Medicine (pp. 31–34).

3. Cootes, T. F., Hill, A., Taylor, C. J., & Haslam, J. (1994). Use of active shape models for locating structures in medical images. Image and Vision Computing, 12(6), 355–365.

4. Dai, W., Doyle, J., Liang, X., Zhang, H., Dong, N., Li, Y., & Xing, E. P. (2017). SCAN: Structure correcting adversarial network for chest X-rays organ segmentation. arXiv preprint arXiv:1703.08770.

5. Dawoud, A. (2010). Fusing shape information in lung segmentation in chest radiographs. Image Analysis and Recognition, 6112, 70–78.

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