Auxílio à Classificação de Nódulos Pulmonares usando Recuperação de Imagens Similares baseada em Análise de Textura 3D e Registro de Imagem 3D
Resumo
O objetivo deste trabalho foi desenvolver um algoritmo para auxiliar especialistas na classificação de nódulos pulmonares. A motivação deste trabalho advém também pelo fato de acreditarmos que uma solução computacional precisa, robusta e amistosa possa incentivar o diagnóstico auxiliado por computador que se constitui numa forma efetiva de reduzir o grande volume de impressão em filme radiológico. As técnicas de Análise de Textura 3D e Registro de Imagem 3D (RI) foram desenvolvidas como métodos de recuperação de imagens similares (CBIR). A precisão média dos algoritmos foi superior a 70%. Os resultados do RI são inéditos na literatura e evidenciaram o potencial futuro da técnica como método de CBIR.Referências
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Haralick, R. M., Shanmuga.K, et al. (1973) "Textural Features for Image Classification". IEEE Transactions on Systems Man and Cybernetics, v.SMC3, n.6, p.610-621.
Lam Mo, D. T., Raicu Ds, Furst J, Channin Ds. (2007) "BRISC-an open source pulmonary nodule image retrieval framework.". Journal of Digital Imaging, v.20, p.5.
Lehmann, T. M., T. M. Lehmann, et al. Content-based image retrieval in medical applications: A novel multi-step approach Proc. SPIE: SPIE--The International Society for Optical Engineering, 1999. p.312-320.
Li, Q. (2007) "Recent progress in computer-aided diagnosis of lung nodules on thin-section CT". Computerized Medical Imaging and Graphics, v.31, n.4-5, p.248-257.
Mcnitt-Gray, M. F., S. G. Armato, et al. (2007) "The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation". Academic Radiology, v.14, p.1464-1474.
Muller, H., N. Michoux, et al. (2004) "A review of content-based image retrieval systems in medical applications - clinical benefits and future directions". International Journal of Medical Informatics, v.73, n.1, p.1-23.
Olabarriaga, S. D., J. G. Snel, et al. (2007) "Integrated support for medical image analysis methods: From development to clinical application". Ieee Transactions on Information Technology in Biomedicine, v.11, n.1, p.47-57.
Oliveira, M. C., W. Cirne, et al. (2007) "Towards applying content-based image retrieval in the clinical routine". Future Generation Computer Systems, v.23, n.3, p.466-474.
Pietka, E., A. Gertych, et al. (2005) "Informatics infrastructure of CAD system". Computerized medical imaging and graphics, v.29, p.157-169.
Rahman, M., T. Wang, et al. Medical Image Retrieval and Registration: Towards Computer Assisted Diagnostic Approach. IDEAS Workshop on Medical Information Systems: The Digital Hospital (IDEAS-DH'04). Los Alamitos, CA, USA: IEEE Computer Society, 2004. p.78-89.
Silverman, E. K. S., F.E. (1996) "Risk factors for the development of chronic obstructive pulmonary disease.". Med Clin North Am, v.80, p.501-22.
Sluimer, I., A. Schilham, et al. (2006) "Computer analysis of computed tomography scans of the lung: A survey". IEEE Transactions on Medical Imaging, v.25, n.4, p.385-405.
Takashima, S., S. Sone, et al. (2003) "Indeterminate solitary pulmonary nodules revealed at population-based CT screening of the lungs: Using first follow-up diagnostic CT to differentiate benign and malignant lesions". American Journal of Roentgenology, v.180, n.5, p.1255-1263.
Traina, A. J. M., A. G. R. Balan, et al. Content-based image retrieval using approximate shape of objects. IEEE Symposium on Computer-Based Medical Systems (CBMS), 2004.
Yoo, T. (2004) "Insight into images: principles and practice for segmentation, registration and image analysis". AK Peters LTDA, v.1. 350 p., Massachusetts, USA.
Publicado
20/07/2010
Como Citar
AYRES, Pedro Augusto; BEZERRA, Rodolfo Carneiro; OLIVEIRA, Marcelo Costa.
Auxílio à Classificação de Nódulos Pulmonares usando Recuperação de Imagens Similares baseada em Análise de Textura 3D e Registro de Imagem 3D. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 10. , 2010, Belo Horizonte/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2010
.
p. 1665-1672.
ISSN 2763-8952.
