Fuzzy Information Granulation on Blood Vessel Extraction from 3D TOF MRA Image

Fuzzy Information Granulation on Blood Vessel Extraction from 3D TOF MRA Image
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3D TOF MRA 图像血管提取的模糊信息粒化

DOI:
10.1142/s0218001400000271
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发表时间:
2000
期刊:
Int. J. Pattern Recognit. Artif. Intell.
影响因子:
--
通讯作者:
F. Miyawaki
F. Miyawaki
中科院分区:
--
文献类型:
--
作者:
Syoji Kobashi;N. Kamiura;Y. Hata;F. Miyawaki

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将模糊信息粒化算法(FUZZY IG)应用于医学图像分割。模糊IG是从信息中派生出模糊粒。在医学图像分割的情况下,信息和模糊颗粒分别对应于从医学扫描仪获取的图像和解剖部分,即感兴趣区域(ROI)。该方法由体积量化和模糊合并两部分组成。体积量化是指收集相似的相邻体素。根据表示医学图像的解剖知识的预定义模糊模型的程度来选择性地合并所生成的量子。将该方法应用于脑部三维飞行时间(TOF)磁共振血管成像(MRA)图像的血管提取。本文所研究的体数据由大约100幅连续的和体积的MRA图像组成。根据模糊免疫球蛋白的概念,信息对应于体积数据,模糊颗粒对应于血管和脂肪。医生对从所获得的血管生成的二维和三维图像进行定性评估。评价结果表明,该方法能够分割MRA体数据,模糊免疫算法适用于医学图像分割,适合医学图像分割。
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