Title :
Computer simulation for segmentation of lung nodules in CT images
Author :
Dajnowiec, Maciej ; Alirezaie, Javad
Author_Institution :
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, Ont.
Abstract :
Automated lung nodule detection through computed tomography (CT) image segmentation is a new and exciting research area of medical image processing. We are currently developing a nodule detection system. For the testing stage we have developed a method to insert simulated lung nodules into CT images. The simulated nodules can be used to produce corner cases to provide a better test environment for the segmentation technique than would be available through clinical data. The synthetic lung nodules produced by this program are based on a 2D Gaussian structure. This is modeled on the study of the structure of real lung nodules. We have also developed a lung segmentation technique, which is the first stage of our nodule detection system. The lungs are segmented using a combination of thresholding, morphology, 3D region growing, and volume analysis
Keywords :
Gaussian processes; computerised tomography; image segmentation; lung; medical image processing; 2D Gaussian structure; CT images; computed tomography image segmentation; lung nodules segmentation; medical image processing; nodule detection system; Cancer detection; Computational modeling; Computed tomography; Computer simulation; Diagnostic radiography; Image segmentation; Lungs; Medical simulation; Robustness; Testing;
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-7803-8566-7
DOI :
10.1109/ICSMC.2004.1401239