Computer-aided diagnosis of small pulmonary nodules.
Computer-aided methods are now being developed for the detection and characterization of pulmonary nodules found in CT images, based on techniques from computer vision, image processing, and pattern classification. With the increasing resolution of modern CT scanners, computer methods provide continually improving accuracy, reproducibility, and utility in analyzing the larger numbers of images acquired in a lung screening exam or diagnostic study. This article describes the fundamental tools and issues involved in computer-aided nodule detection and characterization, as we move from two-dimensional toward three-dimensional automated methods. In particular, we focus on the new domain of "small" pulmonary nodules.
Reeves
A P
AP
School of Electrical Engineering, Cornell University, Ithaca, NY 14853, USA.
Kostis
W J
WJ
D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D010363:Pattern Recognition, Automated; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D015898:Tomography Scanners, X-Ray Computed; D014057:Tomography, X-Ray Computed