Application of the iris filter for automatic detection of pulmonary nodules on computed tomography images.
We have developed a computer-aided diagnosis (CAD) system to detect pulmonary nodules on thin-slice helical computed tomography (CT) images. We have also investigated the capability of an iris filter to discriminate between nodules and false-positive findings. Suspicious regions were characterized with features based on the iris filter output, gray level and morphological features, extracted from the CT images. Functions calculated by linear discriminant analysis (LDA) were used to reduce the number of false-positives. The system was evaluated on CT scans containing 77 pulmonary nodules. The system was trained and evaluated using two completely independent data sets. Results for a test set, evaluated with free-response receiver operating characteristic (FROC) analysis, yielded a sensitivity of 80% at 7.7 false-positives per scan.
Suárez-Cuenca
Jorge Juan
JJ
Department of Radiology, University of Santiago de Compostela (CHUS), Spain. jorgejuan.suarez@usc.es
Tahoces
Pablo G
PG
Souto
Miguel
M
Lado
María J
MJ
Remy-Jardin
Martine
M
Remy
Jacques
J
Vidal
Juan José
JJ
D000465:Algorithms; D001331:Automation; D016002:Discriminant Analysis; D005189:False Positive Reactions; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D012372:ROC Curve; D014057:Tomography, X-Ray Computed / Q000379:methods*