Dynamic contrast enhanced magnetic resonance imaging parameter based computer assisted diagnostic tool using three random variable co-occurrence approach.
作者： Bradley D. Clymer , Johannes T. Heverhagen , Michael V. Knopp , Mehmet C. Kale
DOI:
关键词: Dynamic contrast 、 Random variable 、 Artificial intelligence 、 Execution time 、 Joint (audio engineering) 、 Breast tissue 、 Computer vision 、 Algorithm 、 Magnetic resonance imaging 、 Computer science
摘要: In this research we describe an implementation of the joint statistical co-occurrence analysis 3 types dynamic contrast enhanced magnetic resonance (DCE-MR) images breast tissue for detection tumors. The method was implemented in distributed and parallel environments to decrease long execution time caused by huge size data. This is first known on pharmacokinetic data also multiimage medical applications.
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