Paper
6 June 2000 Improved method for automatic identification of lung regions in chest radiographs
Yang Zheng, Lihua Li, Maria Kallergi, Wei Qian, Robert A. Clark M.D.
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Abstract
An algorithm is developed for fast, accurate identification of lung fields in chest radiographs for use in various computer- aided diagnosis (CAD) schemes. The method we presented simplifies the current approach of edge detection from derivatives by using only the first derivative of the profiles of each image, and combining it with pattern classification and image feature analysis in determining both the region of interest (ROI) and the actual lung boundaries. Moreover, instead of using the traditional curve fitting to delineate the detected lung field, we applied an iterative contour smoothing algorithm to each of the four detected boundary segments (lateral, medial, top and diaphragm edges) to form a closed smooth boundary for each lung. These improvements result in dramatic reduction of the running time and more accurate boundary detection, especially the diaphragm edges. The proposed algorithm has been tested with 40 posterior- anterior (PA) chest images. The detected left and right lung fields have an averaged accuracy of over 95%.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yang Zheng, Lihua Li, Maria Kallergi, Wei Qian, and Robert A. Clark M.D. "Improved method for automatic identification of lung regions in chest radiographs", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); https://doi.org/10.1117/12.387619
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CITATIONS
Cited by 13 scholarly publications.
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KEYWORDS
Lung

Image segmentation

Chest imaging

Algorithm development

Chest

Image analysis

Edge detection

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