Computer-aided detection of pulmonary nodules using dynamic self-adaptive template matching and a FLDA classifier

Computer-aided detection of pulmonary nodules using dynamic self-adaptive template matching and a FLDA classifier

Highlights • A new CAD scheme for pulmonary nodule detection is proposed. • Dynamic self-adaptive template matching is used to detect nodules. • FLDA classifier can filter false positive detection nodules.

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Physica medica 2016-12, Vol.32 (12), p.1502-1509
Hauptverfasser: Gong, Jing, Liu, Ji-yu, Wang, Li-jia, Zheng, Bin, Nie, Sheng-dong
Format: Artikel
Sprache:eng
Schlagworte:
Computer-aided detection
CT images
Discriminant Analysis
False Positive Reactions
FLDA
Humans
Image Processing, Computer-Assisted
Linear Models
Lung Neoplasms - diagnostic imaging
Pulmonary nodule
Radiographic Image Interpretation, Computer-Assisted - methods
Radiology
Template matching
Tomography, X-Ray Computed
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Highlights • A new CAD scheme for pulmonary nodule detection is proposed. • Dynamic self-adaptive template matching is used to detect nodules. • FLDA classifier can filter false positive detection nodules.
ISSN:1120-1797
1724-191X
DOI:10.1016/j.ejmp.2016.11.001