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基于KFCM-CV模型的Spark分布式医学图像分割方法

Spark distributed medical image segmentation method based on KFCM-CV model

中文摘要英文摘要

医学图像分割对于医疗诊断和病理学研究具有重要意义。为了快速有效的处理医学图像,本文提出了一种基于Spark分布式处理医学图像的方法。在本文中,首先建立了一种基于改进的模糊核聚类和CV模型的医学图像分割模型,然后用Spark对医学图像进行了批量处理,最后进行了模拟实验,其结果表明本文提出的方法实现了高效精确的分割。

Medical image segmentation is great significance for the study of medical diagnosis and pathology. In order to process medical images effectively and quickly, a medical image processing method based on Spark is proposed in this paper. Firstly, a model for medical image segment based on improved fuzzy kernel clustering and CV model is built, then the medical images are processed in batches by using this model and Spark. Simulation experiments show that the method proposed in this paper achieves efficient and accurate segmentation.

郭玉翠、梁靖宜

医学研究方法计算技术、计算机技术生物科学研究方法、生物科学研究技术

计算机应用技术图像分割KFCM-CVSpark

computer applicationimage segmentationkfcm-cvSpark

郭玉翠,梁靖宜.基于KFCM-CV模型的Spark分布式医学图像分割方法[EB/OL].(2017-12-29)[2025-08-21].http://www.paper.edu.cn/releasepaper/content/201712-377.点此复制

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