3D Lung Fissure Segmentation in TC images based in Textures

Among all cancers, lung cancer (LC) is the most common of all malignant tumors. In order to obtain a more effective segmentation of pulmonary fissures, independent to other structures present in the CT scan, this paper proposes the segmentation of 3D fissures using texture measures and Artificial Neural Networks (ANN). The results of this study are based on voxels classified as fissure through the proposed method compared to the gold standard set by an expert. The results were analyzed using similarity coefficient rate of 95.6%, the rate sensitivity of 71.1% and specificity of 95.6% rate. Thus, it is possible to identify the job has a gain due to not using segmentation of other pulmonary structures and does not require the use of pulmonary atlas.

[1]  Fátima N. S. de Medeiros,et al.  Lung disease detection using feature extraction and extreme learning machine , 2014 .

[2]  R.M. Haralick,et al.  Statistical and structural approaches to texture , 1979, Proceedings of the IEEE.

[3]  Paulo César Cortez,et al.  Method of Automatic Initialization of Active Contours Applied to Lungs in Computed Tomography Images , 2013 .

[4]  Paulo César Cortez,et al.  Modelo de Contorno Ativo Crisp: nova técnica de segmentação dos pulmões em imagens de TC , 2011 .

[5]  Victor Hugo C. de Albuquerque,et al.  Novel Adaptive Balloon Active Contour Method based on internal force for image segmentation - A systematic evaluation on synthetic and real images , 2014, Expert Syst. Appl..

[6]  Elizangela Souza Reboucas,et al.  3D Adaptive Balloon Active Contour: method of segmentation of structures in three dimensions , 2015, IEEE Latin America Transactions.

[7]  P. C. Cortez,et al.  3D segmentation and visualization of lung and its structures using CT images of the thorax , 2013 .

[8]  Bram van Ginneken,et al.  Automatic Segmentation of the Pulmonary Lobes From Chest CT Scans Based on Fissures, Vessels, and Bronchi , 2013, IEEE Transactions on Medical Imaging.

[9]  Venkatesh Mahadevan,et al.  Denoising and fissure extraction in high resolution isotropic CT images using Dual Tree Complex Wavelet Transform , 2010, 2010 2nd International Conference on Software Technology and Engineering.

[10]  Pedro Pedrosa Rebouças Filho,et al.  3D Adaptive Balloon Active Contour: method of segmentation of structures in three dimensions , 2015 .

[11]  David Gur,et al.  A Computational Geometry Approach to Automated Pulmonary Fissure Segmentation in CT Examinations , 2009, IEEE Transactions on Medical Imaging.

[12]  Eric A. Hoffman,et al.  Atlas-driven lung lobe segmentation in volumetric X-ray CT images , 2006, IEEE Transactions on Medical Imaging.

[13]  Simon Haykin,et al.  Neural Networks and Learning Machines , 2010 .

[14]  V. Kavitha,et al.  Automatic segmentation of lung lobes and fissures for surgical planning , 2011, 2011 International Conference on Emerging Trends in Electrical and Computer Technology.

[15]  Victor Hugo C. de Albuquerque,et al.  Adaptive Crisp Active Contour Method for Segmentation and Reconstruction of 3D Lung Structures , 2015 .