基于LS-SVM和NSCT检索系统的放射医学图像有效分类

2012 5th International Conference on Computers and Devices for Communication (CODEC) Pub Date : 2012-12-01 DOI:10.1109/CODEC.2012.6509345

M. Chowdhury, S. Das, M. Kundu

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引用次数: 8

摘要

提出了一种基于内容的医学图像检索(CBMIR)系统。采用非下采样轮廓波变换(NSCT)和模糊c均值(FCM)技术构建图像签名，作为图像的代表性特征向量。采用最小二乘支持向量机(LS-SVM)和地球移动距离(EMD)对图像进行分类。对包含31种不同模式的1550张图像的放射图像数据库(DB)的初步研究显示出有希望的结果。

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Effective classification of radiographic medical images using LS-SVM and NSCT based retrieval system

This paper presents a Content Based Medical Image Retrieval (CBMIR) system for diverse collection of radiographic images. Non-Subsampled Contourlet Transform (NSCT) and Fuzzy C-Means (FCM) technique is used to construct the image signature which is used as the image representative feature vector. Least Square-Support Vector Machine (LS-SVM) and Earth Mover's Distance (EMD) is used to classify the images. Preliminary studies on a radiographic image Database (DB) consisting 1550 images of 31 different modalities show promising result.

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2012 5th International Conference on Computers and Devices for Communication (CODEC)

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