基于模糊连通图像分割和几何矩的Web医学图像检索系统

A. Bhagat, M. Atique
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引用次数: 12

摘要

医学图像数据库的规模日益扩大。医学图像有多种分类,如CT扫描、X线、超声、病理、MRI、显微镜等[1]。医生比较与患者相关的先前和当前的医学图像,以提供正确的治疗。医学影像在现代诊断中起着主导作用。需要高效的图像检索工具来从不断增长的大型医学图像数据库中检索所需的图像。这些工具必须以更低的计算复杂度提供更精确的检索结果。本文提出了一种基于DICOM格式的模糊连通图像分割方法,用于Oracle医学图像检索。本文将图像检索技术与所提出的结合几何矩的模糊连通性图像分割技术进行了比较。文中还给出了该算法在Oracle中的实现细节。为了分析目的,我们实现了基于颜色、纹理和形状的特征提取方法。将这些方法与本文提出的算法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Web Based Medical Image Retrieval System Using Fuzzy Connectedness Image Segmentation and Geometric Moments
Medical image database is growing day by day. There are various categories of medical images such as CT scan, X- Ray, Ultrasound, Pathology, MRI, Microscopy, etc [1]. Physicians compare previous and current medical images associated with patients to provide right treatment. Medical Imaging is playing a leading role in modern diagnosis. Efficient image retrieval tools are needed to retrieve the intended images from large growing medical image databases. Such tools must provide more precise retrieval results with less computational complexity. This paper proposed fuzzy connectedness image segmentation for medical image retrieval in Oracle using digital imaging and communications in medicine (DICOM) format. Paper includes the comparison of image retrieval techniques with the proposed fuzzy connectedness image segmentation combined with geometric moment. Paper also gives the implementation details of proposed algorithm in Oracle. For the analysis purpose we have implemented feature extraction methods for color, texture and shape based feature extraction. These methods are compared with the proposed algorithm.
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