



@book {2373,
	title = {Detection of lung nodule candidates in chest radiographs},
	series = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci.},
	volume = {4478 LNCS},
	year = {2007},
	note = {Conference code: 70962Cited By (since 1996): 3Export Date: 21 November 2012Source: ScopusLanguage of Original Document: EnglishCorrespondence Address: Pereira, C.S.; INEB - Instituto de Engenharia Biom{\'e}dica, Laborat{\'o}rio de Sinal e Imagem, Campus FEUP (Faculdade de Engenharia da Universidade do Porto), Rua Roberto Frias, s/n, 4200-465 Porto, Portugal; email: cmsp@fe.up.ptReferences: Wei, J., Hagihara, Y., Shimizu, A., Kobatake, H., Optimal image feature set for detecting lung nodules on chest X-ray images (2002) CARS 2002;Keserci, B., Yoshida, H., Computerized detection of pulmonary nodules in chest radiographs based on morphological features and wavelet snake model (2002) Medical Image Analysis, 6, pp. 431-447; 
Yoshida, H., Local contralateral subtraction based on bilateral symmetry of lung for reduction of false positives in computerized detection of pulmonary nodules, Biomedical Engineering (2004) IEEE Transactions, 51, pp. 778-789; 
Suzuki, K., Shiraishi, J., Abe, H., MacMahon, H., Doi, K., False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network (2005) Academic Radiology, 12, pp. 191-201; 
Schilham, A., van Ginneken, B., Loog, M., Multi-scale Nodule Detection in Chest Radiographs (2003) LNCS, 2878, pp. 602-609. , Ellis, R.E, Peters, T.M, eds, MICCAI 2003, Springer, Heidelberg; 
Schilham, A., van Ginneken, B., Loog, M., A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database (2006) Medical Image Analysis, 10, pp. 247-258; 
Kobatake, H., Hashimoto, S., Convergence index filter for vector fields (1999) IEEE Transactions on Image Processing, 8 (8); 
Shiraishi, J., Katsuragawa, S., Kezoe, S., Matsumoto, T., Kobayashi, T., Komatsu, K., Matsui, M., Doi, K., Development of a Digital Image Database for Chest Radiographs With and Without a Lung Nodule: Receiver Operating Characteristic Analysis of Radiologists{\textquoteright} Detection of Pulmonary Nodules (2000) American Journal of Roentgenology, 174, pp. 71-74; 
Kobatake, H., Murakami, M., Adaptive filter to detect rounded convex regions: Iris filter (1996) Int. Conf. Pattern Recognition, 11, pp. 340-344; 
Wei, J., Hagihara, Y., Kobatake, H.: Detection of cancerous tumors on chest X-ray images - Candidate detection filter and its evaluation, ICIP99, no. 27AP4.2 (1999)Kobatake, H., Wei, J., Yoshinaga, Y., Hagihara, Y., Shimizo, A., Nonlinear Adaptine Convergence Index Filters and Their Characteristics (2000) Int. Conf. Pattern Recognition, pp. 522-525
},
	month = {2007///},
	pages = {170 - 177},
	address = {Girona},
	abstract = {This paper presents an automated method for the selection of a set of lung nodule candidates, which is the first stage of a computeraided 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. {\textcopyright} Springer-Verlag Berlin Heidelberg 2007.},
	keywords = {Blood Vessels, Computer aided diagnosis, Database systems, Lung nodule candidates, Non-overlapping areas, Pulmonary diseases, Pulmonary nodules, Radiography, Sliding band filter (SBF)},
	isbn = {03029743 (ISSN); 9783540728481 (ISBN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-38049105791\&partnerID=40\&md5=9af5e55fe146cd0455d2302e5383e14c},
	author = {Pereira, C.S. and Fernandes, H. and Mendon{\c c}a, A.M. and Campilho, A.}
}
