A New Method for Medical Image Retrieval Based on Markov Random Field

• 作者: Haiwei Pan Tiaodi Wang Xiaoning Feng Xiaoqin Xie Zhiqiang Zhang
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: Medical image RETRIEVAL MARKOV RANDOM field BELIEF PROPAGATION
• 年，卷（期）: 2017,（1）
• 页码范围: 113-115
• 页数: 3页
• 分类号: C5

摘要

The development of medical images acquisition and storage technology has led to the rapid growth of the relevant data.Retrieval of similar medical images can effectively help doctors to diagnose diseases more accurately.But because of the particularity of medical images,traditional contentbased image retrieval(CBIR)method such as bag-of-words(BOW)cannot be applied to medical images.For example,when retrieving a diseased image,we should not only consider the similar characteristics but also need to consider the type of lesion.And for medical images,images with the same lesion may have different image features,similar images may have different types of lesions.In this paper,a Markov random field(MRF)is structured,and an approximate belief propagation algorithm is used to retrieval images.An adjust-ranking step after initial retrieval is incorporated to further improve the retrieval performance.This paper uses the real brain CT images.The experimental results show that the proposed method can significantly improve the retrieval accuracy and has good efficiency.