Image processing algorithm of computer-aided diagnosis in lung cancer screening by CT

Abstract

SUMMARYThis paper presents a systematic overview of our work for more than a decade on image-processing algorithms for lung cancer screening by CT. Most of the images handled at the mass-screening level are normal cases, and the rate of detection of lung tumors is no more than a few percent. In order to detect such rare tumors with high accuracy, there must be a technique that can correctly detect small changes in the image. On the other hand, the problem can arise that a large number of normal tissues are incorrectly detected. This paper outlines the image-processing algorithm developed by us to correctly detect tumors while reducing overdetection. In particular, we describe in detail the principles and properties of quoit filtering, which was devised for accurate detection of tumors in the first stage.