Pham Tuan D
School of Engineering and Information Technology, University of New South Wales, Canberra ACT 2600, Australia.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:3150-3. doi: 10.1109/IEMBS.2010.5627188.
Automated image detection of white matter changes of the brain is essentially helpful in providing a quantitative measure for studying the association of white matter lesions with other types of biomedical data. Such study allows the possibility of several medical hypothesis validations which lead to therapeutic treatment and prevention. This paper presents a new clustering-based segmentation approach for detecting white matter changes in magnetic resonance imaging with particular reference to cognitive decline in the elderly. The proposed method is formulated using the principles of fuzzy c-means algorithm and geostatistics.
大脑白质变化的自动图像检测对于提供一种定量测量方法以研究白质病变与其他类型生物医学数据之间的关联至关重要。这样的研究使得多种医学假设验证成为可能，进而促成治疗和预防措施。本文提出了一种基于聚类的新分割方法，用于检测磁共振成像中的白质变化，特别针对老年人的认知衰退情况。所提出的方法是根据模糊c均值算法和地质统计学原理制定的。
