Diagnosis of esophagitis based on face recognition techniques.

Santosh S Saraf, Gururaj R Udupi, Santosh D Hajare
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引用次数: 2

Abstract

Face recognition technology has evolved over years with the Principal Component Analysis (PCA) method being the benchmark for recognition efficiency. The face recognition techniques take care of variation of illumination, pose and other features of the face in the image. We envisage an application of these face recognition techniques for classification of medical images. The motivating factor being, given a condition of an organ it is represented by some typical features. In this paper we report the use of the face recognition techniques to classify the type of Esophagitis, a condition of inflammation of the esophagus. The image of the esophagus is captured in the process of endoscopy. We test PCA, Fisher Face method and Independent Component Analysis techniques to classify the images of the esophagus. Esophagitis is classified into four categories. The results of classification for each method are reported and the results are compared.

Abstract Image

Abstract Image

Abstract Image

基于人脸识别技术的食管炎诊断。
人脸识别技术经过多年的发展,主成分分析(PCA)方法是识别效率的基准。人脸识别技术考虑到图像中人脸的光照、姿态和其他特征的变化。我们设想将这些人脸识别技术应用于医学图像的分类。激励因素是,给定一个器官的状况,它是由一些典型的特征来表示的。在本文中,我们报告了使用面部识别技术来分类食管炎的类型,这是一种食道炎症的情况。食管的图像是在内镜检查过程中拍摄的。我们测试了PCA、Fisher Face法和独立分量分析技术来对食管图像进行分类。食管炎分为四类。报告了每种方法的分类结果,并对结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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