A Fully Automatic Method for Lung Parenchyma Segmentation and Repairing

Considering that the traditional lung segmentation algorithms are not adaptive for the situations that most of the juxtapleural nodules, which are excluded as fat, and lung are not segmented perfectly. In this paper, several methods are comprehensively utilized including optimal iterative threshold, three-dimensional connectivity labeling, three-dimensional region growing for the initial segmentation of the lung parenchyma, based on improved chain code, and Bresenham algorithms to repair the lung parenchyma. The paper thus proposes a fully automatic method for lung parenchyma segmentation and repairing. Ninety-seven lung nodule thoracic computed tomography scans and 25 juxtapleural nodule scans are used to test the proposed method and compare with the most-cited rolling-ball method. Experimental results show that the algorithm can segment lung parenchyma region automatically and accurately. The sensitivity of juxtapleural nodule inclusion is 100 %, the segmentation accuracy of juxtapleural nodule regions is 98.6 %, segmentation accuracy of lung parenchyma is more than 95.2 %, and the average segmentation time is 0.67 s/frame. The algorithm can achieve good results for lung parenchyma segmentation and repairing in various cases that nodules/tumors adhere to lung wall.

[1]  L. Hedlund,et al.  Two methods for isolating the lung area of a CT scan for density information. , 1982, Radiology.

[2]  H. K. Huang,et al.  Pattern classification approach to segmentation of digital chest radiographs and chest CT image slices , 1994, Medical Imaging.

[3]  S. Armato,et al.  Computerized detection of pulmonary nodules on CT scans. , 1999, Radiographics : a review publication of the Radiological Society of North America, Inc.

[4]  Eric A. Hoffman,et al.  Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images , 2001, IEEE Transactions on Medical Imaging.

[5]  Max A. Viergever,et al.  Computer-aided diagnosis in chest radiography: a survey , 2001, IEEE Transactions on Medical Imaging.

[6]  Hiroshi Fujita,et al.  Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique , 2001, IEEE Transactions on Medical Imaging.

[7]  Lujie Zong.  The Application of Chain Code Sum in the Edge form Analysis , 2002 .

[8]  David Gur,et al.  Automated lung segmentation in X-ray computed tomography: development and evaluation of a heuristic threshold-based scheme. , 2003, Academic radiology.

[9]  Ayman El-Baz,et al.  Automatic Detection and Recognition of Lung Abnormalities in Helical CT Images Using Deformable Templates , 2004, MICCAI.

[10]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .

[11]  S. Armato,et al.  Automated lung segmentation for thoracic CT impact on computer-aided diagnosis. , 2004, Academic radiology.

[12]  Daw-Tung Lin,et al.  Autonomous detection of pulmonary nodules on CT images with a neural network-based fuzzy system. , 2005, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[13]  Anthony J. Sherbondy,et al.  Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detection. , 2005, Radiology.

[14]  Kunio Doi,et al.  Computer-aided diagnosis in chest radiography , 2007, Comput. Medical Imaging Graph..

[15]  Qiang Li,et al.  Recent progress in computer-aided diagnosis of lung nodules on thin-section CT , 2007, Comput. Medical Imaging Graph..

[16]  Zhang Jing.  Identifying for the Convexo-concave of Peripherals Based on Chain Code Difference , 2007 .

[17]  Liu Wei.  Automated lung segmentation in serial thoracic high resolution CT images , 2008 .

[18]  Geoffrey D. Rubin,et al.  Adaptive border marching algorithm: Automatic lung segmentation on chest CT images , 2008, Comput. Medical Imaging Graph..

[19]  G. Sheng.  Extraction of Pulmonary Parenchyma in Thoracic CT and Computer Aided Diagnosis , 2008 .

[20]  A. Carvalho,et al.  Automatic Lung Segmentation of Helical-CT Scans in Experimental Induced Lung Injury , 2009 .

[21]  Sabina Sonia Tangaro,et al.  Automatic Lung Segmentation in CT Images with Accurate Handling of the Hilar Region , 2011, Journal of Digital Imaging.

[22]  Wu Yan.  A method of careful lung segmentation based on CT images , 2010 .

[23]  Xiang Lanxi.  Automated lung segmentation for chest CT images used for computer aided diagnostics , 2011 .