Abstract
The respiratory system of lungs contains airway trees. The detection and segmentation of airways is a challenging job due to noise, volume effect and non-uniform intensity. We present a novel automatic method of lung segmentation and airway detection using morphological operations. Optimal thresholding combined with connected component analysis gives good results for lung segmentation. We describe a quick method of airway detection with grayscale reconstruction performed on four-connected low-pass filtered image. The results are quite satisfactory with some error due to non-uniform intensity and volume effect in the CT image.
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Khanna, A., Londhe, N.D., Gupta, S. (2019). Automatic Lung Segmentation and Airway Detection Using Adaptive Morphological Operations. In: Tanveer, M., Pachori, R. (eds) Machine Intelligence and Signal Analysis. Advances in Intelligent Systems and Computing, vol 748. Springer, Singapore. https://doi.org/10.1007/978-981-13-0923-6_30
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DOI: https://doi.org/10.1007/978-981-13-0923-6_30
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