TY - GEN
T1 - Hybrid CAD scheme for lung nodule detection in PET/CT images
AU - Teramoto, Atsushi
AU - Fujita, Hiroshi
AU - Tomita, Yoya
AU - Takahashi, Katsuaki
AU - Yamamuro, Osamu
AU - Tamaki, Tsuneo
AU - Hayashi, Naoki
AU - Tamai, Shinichi
AU - Nishio, Masami
AU - Chen, Wei Ping
AU - Kobayashi, Toshiki
PY - 2011
Y1 - 2011
N2 - Lung cancer is the leading cause of death among male in the world. PET/CT is useful for the detection of early lung cancer since it is an imaging technique that has functional and anatomical information. However, radiologist has to examine using the large number of images. Therefore reduction of radiologist's load is strongly desired. In this study, hybrid CAD scheme has been proposed to detect lung nodule in PET/CT images. Proposed method detects the lung nodule from both CT and PET images. As for the detection in CT images, solitary nodules are detected using Cylindrical Filter that we developed. PET images are binarized based on standard uptake value (SUV); highly uptake regions are detected. FP reduction is performed using seven characteristic features and Support Vector Machine. Finally by integrating these results, candidate regions are obtained. In the experiment, we evaluated proposed method using 50 cases of PET/CT images obtained for the cancer-screening program. We evaluated true-positive fraction (TPF) and the number of false positives / case (FPs/case). As a result, TPFs for CT and PET were 0.67 and 0.38, respectively. By integrating the both results, TPF was improved to 0.80. These results indicate that our method may be useful for the lung cancer detection using PET/CT images.
AB - Lung cancer is the leading cause of death among male in the world. PET/CT is useful for the detection of early lung cancer since it is an imaging technique that has functional and anatomical information. However, radiologist has to examine using the large number of images. Therefore reduction of radiologist's load is strongly desired. In this study, hybrid CAD scheme has been proposed to detect lung nodule in PET/CT images. Proposed method detects the lung nodule from both CT and PET images. As for the detection in CT images, solitary nodules are detected using Cylindrical Filter that we developed. PET images are binarized based on standard uptake value (SUV); highly uptake regions are detected. FP reduction is performed using seven characteristic features and Support Vector Machine. Finally by integrating these results, candidate regions are obtained. In the experiment, we evaluated proposed method using 50 cases of PET/CT images obtained for the cancer-screening program. We evaluated true-positive fraction (TPF) and the number of false positives / case (FPs/case). As a result, TPFs for CT and PET were 0.67 and 0.38, respectively. By integrating the both results, TPF was improved to 0.80. These results indicate that our method may be useful for the lung cancer detection using PET/CT images.
UR - http://www.scopus.com/inward/record.url?scp=79955757407&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79955757407&partnerID=8YFLogxK
U2 - 10.1117/12.877104
DO - 10.1117/12.877104
M3 - Conference contribution
AN - SCOPUS:79955757407
SN - 9780819485052
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2011
T2 - Medical Imaging 2011: Computer-Aided Diagnosis
Y2 - 15 February 2011 through 17 February 2011
ER -
