计算机科学 ›› 2014, Vol. 41 ›› Issue (Z6): 174-177.

• 模式识别与图像处理 • 上一篇    下一篇

一种食管癌内镜图像识别算法

陈刚,胡振朋,卢红星   

  1. 郑州大学信息工程学院 郑州450001;华南理工大学计算机科学与工程学院 广州510006;郑州大学信息工程学院 郑州450001
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金:多变量IB方法及算法的研究(61170223),河南人才培养联合基金:可扩展迁移学习中跨媒体复杂问题自动映射研究(U1204610)资助

Image Recognition Algorithm for Esophageal Endoscopy

CHEN Gang,HU Zhen-peng and LU Hong-xing   

  • Online:2018-11-14 Published:2018-11-14

摘要: 食管癌内镜检查是食管癌早期诊断的主要手段之一,计算机辅助识别可以大大提高诊断效率,但目前尚缺乏相关识别算法研究。因此,根据食管癌内镜图像的纹理特点,提出了一种食管癌内镜图像识别算法。算法首先对食管癌内镜图像进行目标区域的划分,提取出每个目标子区域的灰度共生矩阵。然后计算灰度共生矩阵的角二阶矩、对比度、逆差分矩和相关度4个特征值,并构造出描述内镜图像的特征向量。最终对特征向量进行多次迭代式聚类并根据专家规则对聚类结果进行筛选以标识出可疑病变区域。实验表明,该算法可以较为准确地筛选出可疑病变区域,算法是可行的和有效的。

关键词: 图像识别,食管癌,内镜,聚类 中图法分类号TP391.7文献标识码A

Abstract: Videoendoscope is an important tool for the diagnosis of esophageal cancer in early stage.Computer aided diagnosis could improve the efficiency.However,there is lack of effective recognition algorithms.Therefore,the paper proposed an image recognition algorithm for esophageal endoscopy (IRAFEE) based on esophageal endoscopic image texture features.Firstly,the IRAFEE algorithm divides the endoscopic image into sub-areas,extracts gray level co-occurrence matrix for each sub-area.Secondly,the IRAFEE algorithm calculates four features of gray level co-occurrence matrix:angle second moment,contrast ratio,inverse difference moment and degree of association,constructs feature vectors.Finally,the IRAFEE algorithm clusters the feature vectors for several times,filters the result clusters based on expert rules and identifies the potential lesion areas.The experiments show that the proposed IRAFE algorithm is feasible and effective.

Key words: Image recognition,Esophageal cancer,Videoendoscope,Cluster

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