Computer-Aided Diagnosis Algorithm for Lung Cancer using Retrospective CT Images

摘要

This paper presents a method for detecting suspicious nodules based on successive low-dose helical CT images. Themethod uses both initial and follow-up images to improve nodule detection performance. The basic idea of the detectionis to register nodule images measured at different time and to assess the changes in size, shape, and density of the nodule.Since there are several variations of nodule changes, such as stable, shrinking, expansion in size, disappearance,appearance, and separation, a coarse-to-fine registration technique was adopted to deal with large nodule deformation.Especially, the fine registration is performed by excluding nodule regions and using nodule surroundings to avoid effectsof nodule deformations in alignment task. In a preliminary experiment, the method was applied to ten cases withsuccessive scans. From visual inspection, the corresponding results between initial and follow-up images wereacceptable in clinical use. More researches using a large data set will be required. Still, we believe that the method hasthe potential of detecting suspicious nodules for use in a computer-aide diagnosis system.