title: Nodule detection in 3D chest CT images using 2nd order autocorrelation features.
abstract: We have developed a new recognition approach using 2nd order autocorrelation and multi-regression analysis to detect a small (<7mm in diameter) lung nodules in chest 3D CT images. By combining our previous detection method of the template matching based on genetic algorithm, the detection performance was 94% true-positive rate at 2.05 false-positive marks per case using leave-one- out study.
authors.affiliation: department of Intelligent Image Information, Graduate School of Medicine, Gifu University, Gifu, Japan. hara@info.gifu-u.ac.jp
authors.forename: T
authors.initials: T
authors.lastname: Hara
authors.forename: M
authors.initials: M
authors.lastname: Hirose
authors.forename: X
authors.initials: X
authors.lastname: Zhou
authors.forename: H
authors.initials: H
authors.lastname: Fujita
authors.forename: T
authors.initials: T
authors.lastname: Kiryu
authors.forename: R
authors.initials: R
authors.lastname: Yokoyama
authors.forename: H
authors.initials: H
authors.lastname: Hoshi