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应用科学学报 ›› 2009, Vol. 27 ›› Issue (5): 480-484.

• 信号与信息处理 • 上一篇    下一篇

医用内窥镜图像校正的BP神经网络方法

王牧云;严壮志;葛俊杰   

  1. 上海大学通信与信息工程学院，上海200072
  • 收稿日期:2009-07-22 修回日期:2009-09-06 出版日期:2009-09-25 发布日期:2009-09-25
  • 通信作者: 严壮志，博士，教授，博导，研究方向：生物医学图像与信息处理，E-mail: zzyan@shu.edu.cn
  • 基金资助:
    上海科技成果转化促进会和上海市教育发展基金会联盟计划基金(No.07LM22)资助项目

Distortion Correction of Medical Endoscopic Images Using BP Neural Network

  1. School of Communication and Information Engineering, Shanghai University, Shanghai 200072, China
  • Received:2009-07-22 Revised:2009-09-06 Online:2009-09-25 Published:2009-09-25

PDF

1590

被引次数

3

摘要：

 用传统的畸变校正法对内窥镜图像进行校正存在畸变模型复杂、计算量大、易产生误差等问题. 该文利用标准模板，提取样本点在标准图像和内窥镜拍摄的畸变图像中的坐标，分别作为BP神经网络训练的输入和目标，通过神经网络的训练拟合成像镜头的畸变模型，从而确定标准图像和畸变图像上像素点的位置关系. 再通过图像插值的方法进行图像恢复，实现图像校正. 实验结果表明该方法简单有效，具有精确性.

关键词: 内窥镜图像, 非线性失真, 畸变校正, BP神经网络

Abstract:

Traditional distortion correction methods for medical endoscopic images have problems such as complication
of distortion modeling, high computation complexity, and susceptibility to errors. The proposed method uses a correction template. Sample coordinates are extracted from the template, and the distorted template image
acquired by the endoscope. These two kinds of extracted coordinates serve respectively as inputs and targets for
training to give the distortion model. Based on the distortion model, a one-to-one correspondence between pixels on the ideal and distorted images is set up. Image correction can then be accomplished by using interpolation. The experimental results show that the proposed method is simple, effective and accurate.

Key words: endoscopic image, nonlinear distortion, distortion correction, BP neural network (BPNN)

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