Abstract

Info

Title:: Automatic archiving of medical images based on feature parameters and cloud model similarity

Author(s):: WU Di1; HU Sheng2; 1. School of Basic Medical Science, Shaanxi University of Chinese Medicine, Xianyang 712046, China 2. School of Mechanical and Electrical Engineering, Xi′an Polytechnic University, Xi′an 710048, China

Keywords:: Keywords: medical image image classification and archiving feature parameter gray level coocurrence matrix cloud model similarity degree

Abstract:: Abstract: An automatic archiving method for medical images is proposed based on feature parameters and cloud model similarity to address the problem of inaccurate image archiving due to low feature contrast. The feature parameters of different images are obtained by extraction of the feature parameters from medical images and image enhancement. Then, the feature images are used to generate cloud droplet feature sets for constructing a ternary image cloud model that can reflect the image characteristics. The cloud model similarity degree is defined, and the similarity of various images to be archived is calculated to realize the automatic classification and archiving of medical images. The experiment confirms that the proposed method can effectively classify medical images automatically, which provide new ideas for the automatic classification and archiving of medical imaging data.