Algorithms and Results in Content-Based Visual Query of the Image Databases Resulting from Dicom Files

L. Stanescu, A. Ion, D. Burdescu, M. Brezovan
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引用次数: 3

Abstract

The article presents a series of algorithms used in the content-based visual query process on databases with color medical images extracted from DICOM files provided by medical tools used in the diagnosis area. Also, the paper presents a detailed study on several directions inside the content-based visual query process. In studying the content-based image query on color feature the transformation from RGB color space to HSV and the quantization at 166 colors was used. For computing the dissimilitude between the query and the target image three metrics were implemented: the Euclidian distance, the histograms intersection and the quadratic distance between histograms. The next study was made on content-based image query on color texture feature. In order to compute the color texture characteristics vectors two methods were implemented: the co-occurrence matrices and Gabor filters. The third studied problem was the content-based region query. For detecting color regions the color set back-projection algorithm was implemented. Statistic studies for this algorithm in keeping track of the patient evolution during the treatment of the peptic ulcers were made
基于内容的Dicom文件图像数据库可视化查询算法与结果
本文介绍了在诊断领域使用的医疗工具提供的DICOM文件中提取彩色医学图像的数据库的基于内容的可视化查询过程中使用的一系列算法。同时,对基于内容的可视化查询过程中的几个方向进行了详细的研究。在研究基于内容的图像色彩特征查询时,采用了RGB色彩空间到HSV的变换和166种颜色的量化。为了计算查询与目标图像之间的差异,实现了三个度量:欧几里得距离、直方图相交和直方图之间的二次距离。接下来研究了基于内容的图像颜色纹理特征查询。为了计算颜色纹理特征向量,实现了两种方法:共现矩阵和Gabor滤波器。研究的第三个问题是基于内容的区域查询。为了检测颜色区域,实现了颜色集反投影算法。对该算法在消化性溃疡治疗过程中对患者进化的跟踪进行了统计研究
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