Computing systems have been playing an important role in various medical fields, notably in image diagnosis. Studies in the field of Computational Vision aim at developing techniques and systems capable of detecting various illnesses automatically. What has been highlighted among the existing exams that allow diagnosis aid and the application of computing systems in parallel is Computed Tomography (CT). CT enables the visualization of internal organs, such as the lung and its structures. Computational Vision systems extract information from the CT images by segmenting the regions of interest, and then recognize and identify details in those images. This work focuses on the segmentation phase of CT lung images with singularity-based techniques. Among these methods are the region growing (RG) technique and its 3D RG variations and the thresholding technique with multi-thresholding. The 3D RG method is applied to lung segmentation and from the 3D RG segments of the lung hilum, the multi-thresholding can segment the blood vessels, lung emphysema and the bones. The results of lung segmentation in this work were evaluated by two pulmonologists. The results ob tained showed that these methods can integrate aid s ystems for medical diagnosis in the pulmonology fie ld.
Keywords3D Region GrowingLungs segmentationCOPDPulmonary Structure VisualizationComputed Tomography
Winkeler, G.F.P. (2006) Effects of noninvasive continuous positive airway pressure on pulmonary inflation in normal subjects in supine and prone positions evaluated by high resolution computed tomography. Master Thesis, Clinical Medicine Department of Federal University of Ceará, Fortaleza.
Fortaleza, S.C.B. (2006) Effect of the administration of continuous positive pressure in aerial ways in not invasive way on the aeration of parenquima pulmonary in patients with pulmonary illness obstrutiva chronicle. Master Thesis, Clinical Medicine Department of Federal University of Ceará, Fortaleza.
Campos, H.S. and Lemos, A.C.M. (2009) Asthma and COPD according to the pulmonologist. Brazilian Journal of Pulmonology, 35, 301-309.
GOLD COPD (2013) Global Strategy for the Diagnosis, Management and Prevention Chronic Obstructive Pulmonary Disease. http://www.goldcopd.org/guidelines-global-strategy-for-diagnosis-management.html
Marco, R., Accordini, S., Cerveri, I., Corsico, A., Sunyer, J., Neukirch, F., Kunzli, N., Leynaert, B., Janson, C., Gislason, T., Vermeire, P., Svanes, C., Anto, J. and Burney, P. (2004) An international survey of chronic obstructive pulmonary disease in young adults according to GOLD stages. Thorax, 59, 120-125. http://dx.doi.org/10.1136/thorax.2003.011163
Felix, J.H.S., Cortez, P.C., Holanda, M.A. and Costa, R.C.S. (2007) Automatic segmentation and measurement of the lungs in healthy persons and in patients with chronic obstructive pulmonary disease in CT images. Proceedings of International Federation for Medical and Biological Engineering, Margarita Island, 24-28 September 2007, 370-373.
Liang, T. K.,Tanaka, T., Nakamura, H., Shirahata, T. and Sugiura, H. (2008) An automated 3D emphysema extraction method using lung CT. SICE Annual Conference, Tokyo, 20-22 August 2008, 3110-3114.
Felix, J.H.S. (2011) 2D Hilbert active contour method to segment lung images from thorax CT. Ph.D. Thesis, Teleinformatic Engineering Department of Federal University of Ceará, Fortaleza.
Sluimer, I., Prokop, M. and van Ginneken, B. (2005) Toward automated segmentation of the pathological lung in CT. IEEE Transactions on Medical Imaging, 24, 1025-1038. http://dx.doi.org/10.1109/TMI.2005.851757
Felix, J.H.S., Cortez, P.C., Holanda, M.A., Albuquerque, V.H.C., Colaco, D.F. and Alexandria, A.R. (2007) Lung and chest wall structures segmentation in CT images. I ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing (VipIMAGE’07), O’Porto, 17-19 October 2007.
Hu, S., Hoffman, E.A. and Reinhardt, J.M. (2001) Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images. IEEE Transactions on Medical Imaging, 20, 490-498. http://dx.doi.org/10.1109/42.929615
Silva, A.C., Carvalho, P.C.P., Nunes, R.A. and Gattass, M. (2006) Segmentation and reconstruction of the pulmonary parenchyma. VI Workshop on Medical Informatics (VI Workshop de Informática Médica), Vila Velha, 29-30 May 2006, 73-82.
Born, S., Iwamaru, D., Pfeifie, M. and Bartz, D. (2009) Three-step segmentation of the lower airways with advanced leakage-control. Second International Workshop on Pulmonary Image Analysis: Extraction of airways from CT (EXACT’09), Pasadena, 11-13 July 2009, 239-250.
Irving, B., Taylor, P. and Todd-Pokropek, A. (2009) 3D segmentation of the airway tree using a morphology based method. Second International Workshop on Pulmonary Image Analysis: Extraction of airways from CT (EXACT’09), Pasadena, 11-13 July, 297-307.
Tschirren, J., Yavarna, T. and Reinhardt, J. (2009) Airway segmentation framework for clinical environments. The Second International Workshop on Pulmonary Image Analysis, London, 20 September 2009, 227-238.
Matsuoka, S., Yamashiro, T., Washko, G. R., Kurihara, Y., Nakajima, Y. and Hatabu, H. (2010) Quantitative CT assessment of chronic obstructive pulmonary disease. Radiographics, 30, 55-66. http://dx.doi.org/10.1148/rg.301095110
Chen, H., Zhang, J., Xu, Y., Chen, B. and Zhang, K. (2012) Performance comparison of artificial neural network and logistic regression model for differentiating lung nodules on CT scans. Expert Systems with Applications, 39, 11503-11509. http://dx.doi.org/10.1016/j.eswa.2012.04.001
Er, O.,Yumusak, N. and Temurtas, F. (2010) Chest diseases diagnosis using artificial neural networks. Expert Systems with Applications, 37, 7648-7655. http://dx.doi.org/10.1016/j.eswa.2010.04.078
Er, O.,Yumusak, N. and Temurtas, F. (2012) Diagnosis of chest diseases using artificial immune system. Expert Systems with Applications, 39, 1862-1868. http://dx.doi.org/10.1016/j.eswa.2011.08.064
Fernández, J.M.F., López, E.J.H., Llamas, F.S., Calvillo, A.R., Galeana, P.A.C., Pacheco, G.L., Palomar., M.G.G., Femat, R. and Velázquez, M.M. (2012) Development of an optimized multi-biomarker panel for the detection of lung cancer based on principal component analysis and artificial neural network modeling. Expert Systems with Applications, 39, 10851-10856. http://dx.doi.org/10.1016/j.eswa.2012.03.008
Annangi, P., Thiruvenkadam, S., Raja, A., Xu, H., Sun., X. and Mao, L. (2010) A region based active contour method for x-ray lung segmentation using prior shape and low level features. Proceedings of 7th IEEE International Symposium on Biomedical Imaging (ISBI), Rotterdam, 14-17 April 2010.
Wu, Y., Wang, Y. and Jia, Y. (2013) Adaptive diffusion flow active contours for image segmentation. Computer Vision and Image Understanding, 117, 1421-1435. http://dx.doi.org/10.1016/j.cviu.2013.05.003
Keshani. M., Azimifar, Z., Tajeripour, F. and Boostani, R. (2013) Lung nodule segmentation and recognition using SVM classifier and active contour modeling: A complete intelligent system. Computers in Biology and Medicine, 43, 287-300. http://dx.doi.org/10.1016/j.compbiomed.2012.12.004
Tan, Y., Schwartz, L. H. and Zhao, B. (2013) Segmentation of lung lesions on CT scans using watershed, active contours, and Markov random field. Medical Physics, 40, 043502. http://dx.doi.org/10.1118/1.4793409
Liu, L. and Bovik, A.C. (2012) Active contours with neighborhood-extending and noise-smoothing gradient vector flow external force. EURASIP Journal on Image and Video Processing, 9, 2-6.
Toshiba (1997) Operation manual of system: X-ray computerized tomography for all body: Calibration data acquisition. Sao Paulo.
Gevenois, P.A. and Yernault, J.C. (1995) Can computed tomography quantify pulmonary emphysema? European Respiratory Journal, 5, 843-848.
Vieira, S.R., Puybasset, L., Richecoeur, J., Lu, Q., Cluzel, P., Gusman, P.B., Coriat, P. and Rouby, J.J. (1998) A lung computed tomographic assessment of positive endexpiratory pressure-induced lung over distension. American Journal of Respiratory and Critical Care Medicine, 158, 1571-1577. http://dx.doi.org/10.1164/ajrccm.158.5.9802101
Gonzalez, R. C. and Woods, R. (2010) Digital image processing. 3rd Edition, Pearson Prentice Hall, New Jersey.
Papamarkos, N., Strouthopoulos, C. and Andreadis, I. (2000) Multithresholding of color and grey-level images through a neural network technique. Image and Vision Computing, 18, 213-222. http://dx.doi.org/10.1016/S0262-8856(99)00015-3
Zahara, E., Fan, S.K.S. and Tsai, D.M. (2005) Optimal multi-thresholding using a hybrid optimization approach. Pattern Recognition Letters, 26, 1082-1095. http://dx.doi.org/10.1016/j.patrec.2004.10.003
Reboucas Filho, P.P., Cortez, P.C. and Holanda, M.A. (2011) Active contour modes Crisp: New technique for segmentation the lungs in CT images. Brazilian Journal of Biomedical Engineering, 27, 259-272.
Cavalcante, T.S. (2010) Technique for automatic segmentation of the airway from thorax CT images. Master Thesis, Teleinformatic Engineering Department of Federal University of Ceará, Fortaleza.
Congalton, R.G. and Green, K. (2008) Assessing the accuracy of remotely sensed data: Principles and practices. 2nd Edition, CRC Press-Taylor & Francis Group. http://dx.doi.org/10.1201/9781420055139
Figueiredo, G.C. and Vieira, C.A.O. (2007) Study of the behavior of Overall Accuracy, Kappa and Tau indexes, commonly used to evaluate the classification of remote sensing images. Proceedings of XIII Brazilian Symposium of Remote Sensing, Florianópolis, 21-26 April, 5755-5762.
Deng-hui, Z., Han-Kui, Z., Bin, X., Zhao-quan, H., Le, Y. and Yun-yun, C. (2010) Analysis of image fusion and classification for high resolution SAR data on-line. 2nd International Conference on Education Technology and Computer (ICETC’10), 22-24 June, Shanghai, V1-267-V1-271.
Can, A., Bello, M.O. and Gerdes, M.J. (2010) Quantification of subcellular molecules in tissue microarray. 20th International Conference on Pattern Recognition, Istanbul, 23-26 August 2010, 2548-2551. http://dx.doi.org/10.1109/ICPR.2010.624
Dundar, M.M., Badve, S., Bilgin, G., Raykar, V., Jain, R., Sertel, O. and Gurcan, M.N. (2011) Computerized classification of intraductal breast lesions using histopathological images. IEEE Transactions on Biomedical Engineering, 58, 1977-1984. http://dx.doi.org/10.1109/TBME.2011.2110648
Engelke, U., Pitrey, Y. and Callet, P.L. (2011) Towards an inter-observer analysis framework for multimedia quality assessment. Third International Workshop on Quality of Multimedia Experience (QoMEX), Mechelen, 7-9 September 2011, 183-188.