Fuzzy Information Granulation on Blood Vessel Extraction from 3D TOF MRA Image
Fuzzy Information Granulation on Blood Vessel Extraction from 3D TOF MRA Image
复制标题
3D TOF MRA 图像血管提取的模糊信息粒化
DOI:
10.1142/s0218001400000271
复制
发表时间:
2000
期刊:
影响因子:
--
通讯作者:
F. Miyawaki
中科院分区:
文献类型:
--
作者:
Syoji Kobashi;N. Kamiura;Y. Hata;F. Miyawaki
This paper shows an application of fuzzy information granulation (fuzzy IG) to medical image segmentation. Fuzzy IG is to derive fuzzy granules from information. In the case of medical image segmentation, information and fuzzy granules correspond to an image taken from a medical scanner, and anatomical parts, namely region of interests (ROIs), respectively. The proposed method to granulate information is composed of volume quantization and fuzzy merging. Volume quantization is to gather similar neighboring voxels. The generated quanta are selectively merged according to degrees for pre-defined fuzzy models that represent anatomical knowledge of medical images. The proposed method was applied to blood vessel extraction from three-dimensional time-of-flight (TOF) magnetic resonance angiography (MRA) images of the brain. The volume data studied in this work is composed of about 100 contiguous and volumetric MRA images. According to the fuzzy IG concept, information correspond to the volume data, fuzzy granules corresponds to the blood vessels and fat. The qualitative evaluation by a physician was done for two- and three-dimensional images generated from the obtained blood vessels. The evaluation shows that the method can segment MRA volume data, and that fuzzy IG is applicable to, and suitable for medical image segmentation.
DOI:
10.1109/34.87344
发表时间:
1991-06-01
影响因子:
23.6
作者:
VINCENT, L;SOILLE, P
通讯作者:
SOILLE, P