Abstract
The vast amount of image data acquired during a thoracic computed tomography (CT) scan makes lung nodule detection a burdensome task. Moreover, the expanding role of CT as a diagnostic imaging modality and the growing acceptance of low-dose CT protocols for lung cancer screening promise to further impact radiologists' workloads. This increase in the number of CT studies being performed combined with multi-slice scanners that yield a greater number of images per study makes computerized analysis of CT images a practical necessity. Computer-aided detection of lesions is already a clinical reality in mammographic breast cancer screening, and such methods are expected to achieve similar success in CT lung cancer screening programs due to the potential for oversight errors on the part of human observers. This paper presents the rationale for computerized analysis of thoracic CT images, reviews the current state of automated lung nodule detection methods for CT, identifies issues that investigators must address, and speculates on future advances.
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