Automatic extraction of ground-glass opacity shadows on CT images of the thorax by correlation between successive slices

In general, segmentation is difficult because surrounding soft tissues and organs have similar CT values and sometimes contact with each other. We propose a new technique for automatic segmentation of lung regions and its classification for ground-glass opacity from the segmented lung regions by computer based on a set of the thorax CT images. In this paper, we segment the lung region for extraction of the region of interest employing binarization and labeling process from the inputted each slices images. The region having the largest area is regarded as the tentative lung regions. Furthermore, the ground-glass opacity is classified by correlation distribution on the slice to slice from the extracted lung region with respect to the thorax CT images. Experiment is performed employing twenty six thorax CT image sets and 96% of recognition rates were achieved. Obtained results are shown along with a discussion

[1]  Wallace T Miller,et al.  Isolated diffuse ground-glass opacity in thoracic CT: causes and clinical presentations. , 2005, AJR. American journal of roentgenology.

[2]  Milan Sonka,et al.  Medical Imaging 2002: Image Processing , 2002 .

[3]  Kunio Doi,et al.  Computer-assisted detection of pulmonary embolism , 2000, Medical Imaging: Image Processing.

[4]  Scott T. Acton,et al.  Merging parametric active contours within homogeneous image regions for MRI-based lung segmentation , 2003, IEEE Transactions on Medical Imaging.

[5]  K. Doi,et al.  Computer-aided diagnosis in radiology: potential and pitfalls. , 1999, European journal of radiology.

[6]  Hyoungseop Kim,et al.  Automatic Extraction of Gound-glass Opacities on Lung CT Images by Histogram Analysis , 2003 .

[7]  Alejandro F. Frangi,et al.  Active shape model segmentation with optimal features , 2002, IEEE Transactions on Medical Imaging.

[8]  Kunio Doi,et al.  Computerized detection of pulmonary embolism in spiral CT angiography based on volumetric image analysis , 2002, IEEE Transactions on Medical Imaging.

[9]  Michael F. McNitt-Gray,et al.  Method for segmenting chest CT image data using an anatomical model: preliminary results , 1997, IEEE Transactions on Medical Imaging.

[10]  M. Giger,et al.  Digital image subtraction of temporally sequential chest images for detection of interval change. , 1994, Medical physics.

[11]  J. Austin,et al.  Glossary of terms for CT of the lungs: recommendations of the Nomenclature Committee of the Fleischner Society. , 1996, Radiology.

[12]  S Katsuragawa,et al.  Image feature analysis and computer-aided diagnosis in digital radiography: detection and characterization of interstitial lung disease in digital chest radiographs. , 1988, Medical physics.

[13]  Mitsuomi Matsumoto,et al.  A detection method of ground glass opacities from chest X-ray CT images , 2002 .