文章基本信息

标题：A GA-based image alignment approach for tissue image matching
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作者：Ting-Hsuan Chen ; Jiun-Hung ; Fang-Jung Shiou 等
期刊名称：Scientific Research and Essays
印刷版ISSN：1992-2248
出版年度：2011
卷号：6
期号：4
页码：887-895
DOI：10.5897/SRE10.902
语种：English
出版社：Academic Journals
摘要：Tissue image matching is important in tissue microarray (TMA) processing, during which massive patient samples are embedded in a single paraffin-based block for simultaneous analysis of pathological features. Prior to TMA processing, the images of the donor block and the corresponding slide must be aligned to determine the desired punching locations. This study developed a genetic algorithm (GA)-based image alignment approach to image superimposition. The similarity between the two images is first evaluated by calculating the dissimilarity area of their binary images using logical operators. The GA is then performed to obtain the optimal translation and rotation parameters for superimposing one image onto another. Experimental results revealed that with both crossover and mutation rates of 0.9, the proposed approach can yield a parameter combination that achieves 100% success of tissue image matching with minimum alignment error.
关键词：Tissue microarray; image alignment; similarity; dismatch factor; genetic algorithm