APPLICATION OF NEW RETRIEVAL METHODS IN MICROSCOPIC MEDICAL IMAGES AND CT IMAGES

Abstract

Medical image retrieval is of great significance for forming correct medical judgments during the diagnosis and treatment process. In response to the fact that there are rich types of features in medical images, this paper constructs a multi-feature fusion model and applies it to medical image retrieval. This multi-feature fusion model utilizes three features. Color information is characterized using three different moments, texture information is obtained using the LBP (Local Binary Pattern) operator, and shape information is described using Hu moments. After collecting three features of medical images, they are fused into a similarity measure model through a self-set weight structure for comparison in medical image retrieval. Experiments show that our method has satisfactory image retrieval result for medical images such as endoscopic images and computed tomography (CT) images. Despite the continuous improvement of recall indicators, the proposed method still has high precision.