Title :
Medical image granulation by fuzzy inference
Author :
Hata, Yutaka ; Hirano, Shoji ; Kamiura, Naotake
Author_Institution :
Dept. of Comput. Eng., Himeji Inst. of Technol., Hyogo, Japan
Abstract :
The paper proposes a scheme of image granulation using the fuzzy inference technique. For a region of interest (ROI) in a medical image, the authors describe knowledge needed to granulate the ROI, for example, knowledge of intensity, location and so on. Generally, one cannot granulate the ROI without employing the whole of the knowledge. Fuzzy inference rules of the derived knowledge can accommodate the granulation. After the inference results are compiled to a total degree, resultant data is obtained. Clustering or a region growing technique is used to granulate the ROI. The experimental results on human brain MR images and human foot CT images show that the method can precisely granulate the ROI
Keywords :
fuzzy logic; image segmentation; inference mechanisms; medical image processing; clustering; fuzzy inference; human brain MR images; human foot CT images; knowledge; medical image granulation; region growing technique; region of interest; Biomedical engineering; Biomedical imaging; Computed tomography; Data visualization; Foot; Fuzzy logic; Gravity; Humans; Image segmentation; Pixel;
Conference_Titel :
Fuzzy Information Processing Society - NAFIPS, 1998 Conference of the North American
Conference_Location :
Pensacola Beach, FL
Print_ISBN :
0-7803-4453-7
DOI :
10.1109/NAFIPS.1998.715562