Automatic detection of lung cancers in chest CT images by variable N-Quoit filter

Abstract

We report the image processing technique for computer-aided diagnosis of the lung cancer screening system by CT (LSCT). LSCT is a mobile-type CT scanner for the mass screening of lung cancer. In this LSCT system, one essential problem is the increase of image information to be diagnosed by a doctor to about 30 slices per patient from 1 X-ray film. To solve this difficult problem, we are trying to reduce the image information drastically to be displayed for the doctor by image processing techniques. We propose a new method named variable new-Quoit filter for the automatic recognition of the pathological shadow candidates. Our computer aided diagnosis (CAD) system can satisfactorily reduce the number of CT cross sections by this method, containing the abnormal shadow candidates.