Abstract
This paper presents an automated method for the selection of a set of lung nodule candidates, which is the first stage of a computer-aided diagnosis system for the detection of pulmonary nodules. An innovative operator, called sliding band filter (SBF), is used for enhancing the lung field areas. In order to reduce the influence of the blood vessels near the mediastinum, this filtered image is multiplied by a mask that assigns to each lung field point an a priori probability of belonging to a nodule. The result is further processed with a watershed segmentation method that divides each lung field into a set of non-overlapping areas. Suspicious nodule locations are associated with the regions containing the highest regional maximum values. The proposed method, whose result is an ordered set of lung nodule candidate regions, was evaluated on the 247 images of the JSRT database with very promising results.
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Pereira, C.S., Fernandes, H., Mendonça, A.M., Campilho, A. (2007). Detection of Lung Nodule Candidates in Chest Radiographs. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72849-8_22
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DOI: https://doi.org/10.1007/978-3-540-72849-8_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72848-1
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