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29 April 2005 Computer-aided diagnosis algorithm for lung cancer using retrospective CT images
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Abstract
This paper presents a method for detecting suspicious nodules based on successive low-dose helical CT images. The method uses both initial and follow-up images to improve nodule detection performance. The basic idea of the detection is 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 effects of nodule deformations in alignment task. In a preliminary experiment, the method was applied to ten cases with successive scans. From visual inspection, the corresponding results between initial and follow-up images were acceptable in clinical use. More researches using a large data set will be required. Still, we believe that the method has the potential of detecting suspicious nodules for use in a computer-aide diagnosis system.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hironori Nakashima, Takuya Yamamoto, Mitsuru Kubo, Yoshiki Kawata, Noboru Niki, Hironobu Ohmatsu, Kenji Eguchi, Hiroyuki Nishiyama, Masahiro Kaneko, Masahiko Kusumoto, Ryutaro Kakinuma D.D.S., and Noriyuki Moriyama "Computer-aided diagnosis algorithm for lung cancer using retrospective CT images", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); https://doi.org/10.1117/12.595591
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