TY - GEN
T1 - Automatic Lung nodule segmentation and classification in CT images based on SVM
AU - Rendon-Gonzalez, Elmar
AU - Ponomaryov, Volodymyr
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/9
Y1 - 2016/8/9
N2 - Early detection of lung cancer is of vital importance to successful treatment where Computed Tomography (CT) screening are considered one of the best methods for detection the early signs of lung cancer. Standard Computer Aided Diagnosis (CAD) systems for Lung cancer detection should employ four steps: preprocessing, lungs parenchyma segmentation, nodule detection and reduction of False Positives (FP). In the proposed approach during the preprocessing step, several masks are calculated using thresholding technique and morphological operations, eliminating this way, background and surrounding tissue. Following, suspicious Regions of Interest (ROI) are calculated using a priori information and Hounsfield Units (HU). During feature extraction, numerous features are calculated in order to restrict the suspicious zones. Finally, Support Vector Machine (SVM) algorithm is employed in classification stage.
AB - Early detection of lung cancer is of vital importance to successful treatment where Computed Tomography (CT) screening are considered one of the best methods for detection the early signs of lung cancer. Standard Computer Aided Diagnosis (CAD) systems for Lung cancer detection should employ four steps: preprocessing, lungs parenchyma segmentation, nodule detection and reduction of False Positives (FP). In the proposed approach during the preprocessing step, several masks are calculated using thresholding technique and morphological operations, eliminating this way, background and surrounding tissue. Following, suspicious Regions of Interest (ROI) are calculated using a priori information and Hounsfield Units (HU). During feature extraction, numerous features are calculated in order to restrict the suspicious zones. Finally, Support Vector Machine (SVM) algorithm is employed in classification stage.
KW - CAD
KW - Computed Tomography
KW - Lung Nodule
KW - SVM
UR - http://www.scopus.com/inward/record.url?scp=84987936789&partnerID=8YFLogxK
U2 - 10.1109/MSMW.2016.7537995
DO - 10.1109/MSMW.2016.7537995
M3 - Contribución a la conferencia
AN - SCOPUS:84987936789
T3 - 9th International Kharkiv Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2016
BT - 9th International Kharkiv Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Kharkiv Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2016
Y2 - 20 June 2016 through 24 June 2016
ER -
