Title :
Graded Retrieval Method Research for Medical Images
Author :
Dong, Yin ; Dongyan, Jia ; Yiyuan, Wang
Author_Institution :
Inf. Process. Center, Univ. of Sci. & Technol. of China, Hefei
Abstract :
Fast, nicely retrieving similar image case from medical image database is very helpful for doctor to detect and make decision in difficulty case. This paper presents a new policy for medical images retrieval based on graded retrieving method. First, the four classical texture features, including texture energy, texture entropy, texture inertial moment and local texture calmness, are calculated by the co-occurrence matrix of the image, and utilized to accomplish the elementary retrieval. Second, the method makes use of the projection vector of the object outline using Canny edge operator to breed out the false alarms of the elementary retrieval and accomplish high-grade retrieval. Experiment results show that the method can achieve fairly high precision and recall.
Keywords :
PACS; content-based retrieval; edge detection; image retrieval; image texture; medical image processing; Canny edge operator; PACS; co-occurrence matrix; content-based medical image retrieval; elementary retrieval; false alarms; graded retrieval method research; high-grade retrieval; medical image database; picture archiving-and-communication system; projection vector; texture calmness; texture energy; texture entropy; texture features; texture inertial moment; Biomedical imaging; Content based retrieval; Feature extraction; Histograms; Image databases; Image retrieval; Information retrieval; Medical treatment; Shape; Spatial databases; Canny Operator; Co-occurrence Matrix; Graded Retrieval; Shape Feature; Texture Feature;
Conference_Titel :
Information Acquisition, 2006 IEEE International Conference on
Conference_Location :
Shandong
Print_ISBN :
1-4244-0528-9
Electronic_ISBN :
1-4244-0529-7
DOI :
10.1109/ICIA.2006.305783