TY - JOUR
T1 - Hybrid method for the detection of pulmonary nodules using positron emission tomography/computed tomography
T2 - A preliminary study
AU - Teramoto, Atsushi
AU - Fujita, Hiroshi
AU - Takahashi, Katsuaki
AU - Yamamuro, Osamu
AU - Tamaki, Tsuneo
AU - Nishio, Masami
AU - Kobayashi, Toshiki
N1 - Funding Information:
Conflict of interest This research is supported in part by “Computational Anatomy for Computer-aided Diagnosis and Therapy: Frontiers of Medical Image Sciences” funded by Grant-in-Aid for Scientific Research on Innovative Areas, MEXT, Japan; in part by Tateishi Science and Technology Foundation, Japan.
PY - 2014/1
Y1 - 2014/1
N2 - Purpose: In this study, an automated scheme for detecting pulmonary nodules using a novel hybrid PET/CT approach is proposed, which is designed to detect pulmonary nodules by combining data from both sets of images. Methods: Solitary nodules were detected on CT by a cylindrical filter that we developed previously, and in the PET imaging, high-uptake regions were detected automatically using thresholding based on standardized uptake values along with false-positive reduction by means of the anatomical information obtained from the CT images. Initial candidate nodules were identified by combining the results. False positives among the initial candidates were eliminated by a rule-based classifier and three support vector machines on the basis of the characteristic features obtained from CT and PET images. Results: We validated the proposed method using 100 cases of PET/CT images that were obtained during a cancer-screening program. The detection performance was assessed by free-response receiver operating characteristic (FROC) analysis. The sensitivity was 83.0 % with the number of false positives/case at 5.0, and it was 8 % higher than the sensitivity of independent detection systems using CT or PET images alone. Conclusion: Detection performance indicates that our method may be of practical use for the identification of pulmonary nodules in PET/CT images.
AB - Purpose: In this study, an automated scheme for detecting pulmonary nodules using a novel hybrid PET/CT approach is proposed, which is designed to detect pulmonary nodules by combining data from both sets of images. Methods: Solitary nodules were detected on CT by a cylindrical filter that we developed previously, and in the PET imaging, high-uptake regions were detected automatically using thresholding based on standardized uptake values along with false-positive reduction by means of the anatomical information obtained from the CT images. Initial candidate nodules were identified by combining the results. False positives among the initial candidates were eliminated by a rule-based classifier and three support vector machines on the basis of the characteristic features obtained from CT and PET images. Results: We validated the proposed method using 100 cases of PET/CT images that were obtained during a cancer-screening program. The detection performance was assessed by free-response receiver operating characteristic (FROC) analysis. The sensitivity was 83.0 % with the number of false positives/case at 5.0, and it was 8 % higher than the sensitivity of independent detection systems using CT or PET images alone. Conclusion: Detection performance indicates that our method may be of practical use for the identification of pulmonary nodules in PET/CT images.
UR - http://www.scopus.com/inward/record.url?scp=84895065936&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84895065936&partnerID=8YFLogxK
U2 - 10.1007/s11548-013-0910-y
DO - 10.1007/s11548-013-0910-y
M3 - Article
C2 - 23793722
AN - SCOPUS:84895065936
SN - 1861-6410
VL - 9
SP - 59
EP - 69
JO - International Journal of Computer Assisted Radiology and Surgery
JF - International Journal of Computer Assisted Radiology and Surgery
IS - 1
ER -
