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Application of distributed computation of texture features to the analysis of biomedical images

机译:分布式计算纹理特征在生物医学图像分析中的应用

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摘要

Medical applications are among the tasks of optical technology. The processing of two-dimensional optical signals and images is an urgent task today. One of the most dangerous eye diseases is diabetic macular retinopathy. The first stage in the laser coagulation operation is the stage of fundus image segmentation. The calculation of texture features for solving this problem takes a lot of time. In this paper, we consider the use of a high-performance algorithm for calculating texture features based on distributed computing to speed up the processing and analysis of medical images. Various use cases of the high-performance algorithm on a single node were investigated and compared with sequential and parallel algorithms. The high-performance algorithm achieves a 40× speedup and more under some parameters. Using a high-performance algorithm, analysis and segmentation is performed in less than 1 minute for standard images. The use of a high-performance algorithm for the analysis and segmentation of fundus images avoids the need for a sequential skip-step algorithm, which, due to interpolation, reduces the execution time, but at the same time, accuracy is lost.
机译:医疗应用是光学技术的任务之一。二维光学信号和图像的处理是今天的紧急任务。最危险的眼部疾病之一是糖尿病黄斑视网膜病变。激光凝固操作中的第一阶段是眼底图像分割的阶段。解决此问题的纹理特征计算需要很多时间。在本文中,我们考虑使用高性能算法来计算基于分布式计算的纹理特征,加快医学图像的处理和分析。研究了单个节点上的高性能算法的各种用例,并与顺序和并行算法进行了比较。高性能算法在某些参数下实现了40倍的加速等。使用高性能算法,分析和分割在不到1分钟的标准图像中执行。使用高性能算法的基底图像的分析和分割避免了对顺序跳过阶梯算法的需求,由于插值,这减少了执行时间,但同时丢失了准确度。

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