IIAE CONFERENCE SYSTEM, The 1st IEEE/IIAE International Conference on Intelligent Systems and Image Processing 2013 (ICISIP2013)

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A Proposal of Pseudo Normal Image Subtraction for Lung Nodule Detection
Moribe Masayuki, Yuriko Tsunoda, Hideaki Orii, Hideaki Kawano, Hiroshi Maeda

Last modified: 2013-10-01

Abstract


In this paper, a novel computer aided detection (CAD) system for lung nodules in a simple chest X-ray is discussed. In the presence of test subject's past image, the lung nodules can be detected comparatively easily by using temporal subtraction method. However, the temporal subtraction cannot be applied in the absence of test subject's past image. In this study, a normal, i.e. focus-free, image at the time of inspection is estimated from a database composed of different subjects' chest X-rays that have been already diagnosed as normal by medical specialists. We call the estimated image as pseudo normal image. We propose a CAD system based on subtraction between the original test image and the pseudo normal image, and also call the CAD system as pseudo normal image subtraction. As a result of experiments with the use of available simple chest X-rays, the relative advantages against for an existing method were suggested. And it became apparent that the proposed method is a promising approach.


Keywords


lung nodule detection, computer-aided detection, CAD, image synthesis

References


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