Computer-assisted detection of pulmonary nodules: preliminary observations using a prototype system with multidetector-row CT data sets.
The continued revolution in multidetector-row CT (MDCT) scanning increases the quality of lung imaging but at the cost of a greater burden of data for review and interpretation. This article discusses our preliminary experience with prototype software for lung nodule detection and characterization using MDCT data sets. We discuss the potential role of computer-assisted detection (CAD) as applied to the automatic detection of lung nodules. We also review the process of CAD, outline its potential results, and explore how it may fit into existing radiology practice. Finally, we discuss MDCT data-acquisition parameters and how they may affect the performance of CAD.
Lawler
Leo P
LP
Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, JHOC 3254, 601 North Caroline Street, Baltimore, MD 21287-0801, USA.
Wood
Susan A
SA
Pannu
Harpreet K
HK
Fishman
Elliot K
EK
Pannu
Harpreet S
HS
D000465:Algorithms; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D010865:Pilot Projects; D011857:Radiographic Image Interpretation, Computer-Assisted; D012680:Sensitivity and Specificity; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods*