Title :
Graph-based medical image clustering
Author :
Jian Li ; Haiwei Pan ; Minghui Zhang ; Qilong Han ; Xiaoning Feng
Author_Institution :
Dept. of Comput. Sci., Harbin Finance Univ., Harbin, China
Abstract :
With the development of medical imaging technology, more and more medical images affect the diagnosis. In order to effectively manage and utilize these medical images, researchers pay more attention on data clustering in medical images. Medical images are very complicated in structure and there are numerous characteristic. Most medical images are multidimensional data. So we convert images into a complete graph as an established form, then accomplish image´ clustering by graph clustering. This method combined with medical knowledge can obtain a good image clustering results that meet the requirements of the medical staff. The experimental results prove that this method has better accuracy.
Keywords :
data mining; feature extraction; graph theory; medical image processing; pattern clustering; graph clustering; graph-based medical image clustering; medical image management; medical image utilization; medical imaging technology; medical knowledge; Medical diagnostic imaging; Clustering; Graph; Medical Image; image mining; retrieval;
Conference_Titel :
Computing and Networking Technology (ICCNT), 2012 8th International Conference on
Conference_Location :
Gueongju
Print_ISBN :
978-1-4673-1326-1