Ανίχνευση οζιδίων του πνεύμονα στην υπολογιστική αξονική τομογραφία χαμηλής δόσης

• Κύριος συγγραφέας: Κορφιάτης, Παναγιώτης
• Άλλοι συγγραφείς: Κωσταρίδου, Ελένη
• Μορφή: Thesis
• Γλώσσα: Greek
• Έκδοση: 2008
• Θέματα: Υπολογιστική αξονική τομογραφία; Καρκίνος του πνεύμονα; Οζίδια; Σύστημα αυτόματης ανίχνευσης; Multi-detector CT; Lung cancer; Nodules; Computer Aided Detection (CAD) system; 616.994 240 75

Use of multi-detector CT in lung cancer screening has the potential to detect smaller lung nodules with improved sensitivity. In this study the development of a Computer Aided Detection (CAD) system for lung nodules is reported. A combination of two segmentation approaches is used, to segment lung regions. Following segmentation, a selective enhancement filter is applied for ''initial'' identification of nodule seed points in lung regions. Candidate lung nodule regions were delineated with the use of a region growing algorithm, with thresholds provided by minimum error thresholding. False positive regions were subsequently removed using two Support Vector Machines (SVM) classifiers in cascade, utilizing a set of 6 morphological features extracted from corresponding nodule candidate regions of the enhanced and the original images. The proposed automated scheme was tested on a reference dataset of 21 cases provided by the Lung Imaging Database Consortium. System performance on a case and slice basis provided sensitivities of 91% and 81% respectively, both with an average of 5 FPs per slice. Further analysis of the slice dataset with respect to size, contrast and location of nodules provided sensitivities of 81%, 83% and 85% for nodules of small size, low contrast and near pleura. This CAD scheme may be a useful tool in assisting radiologists in lung nodule detection.