结合字典学习和稀疏聚类的医学图像分割算法

doi:10.3969/j.issn.0253-2778.2019.10.003

中国科学技术大学学报 ›› 2019, Vol. 49 ›› Issue (10): 791-796.DOI: 10.3969/j.issn.0253-2778.2019.10.003

结合字典学习和稀疏聚类的医学图像分割算法

张滨凯，王翔，郑津津

中国科学技术大学精密机械与精密仪器系，安徽合肥 230027

收稿日期:2018-04-30 修回日期:2019-03-18 接受日期:2019-03-18 出版日期:2019-10-31 发布日期:2019-03-18
通讯作者: 王翔
作者简介:张滨凯,男,1990年生,博士生.研究方向:图形与图像处理.E-mail:bkzhang@mail.ustc.edu.cn
基金资助:
国家自然科学基金联合基金(U1332130),111引智工程(B07033),国家重点基础研究发展计划(973)( 2014CB931804),安徽省重点研究与开发计划(1704a0902051)资助.

Medical image segmentation algorithm based on dictionary learning and sparse clustering

ZHANG Binkai, WANG Xiang, ZHENG Jinjin

Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230027, China

Received:2018-04-30 Revised:2019-03-18 Accepted:2019-03-18 Online:2019-10-31 Published:2019-03-18

摘要/Abstract

摘要： 为了改善医学图像的分割效果，结合字典学习和聚类算法，提出了一种以字典作为聚类中心，以稀疏表示实现聚类分割的医学图像分割算法.对于单幅的医学图像，可以通过交互进行稀疏表示和字典更新至收敛，从而实现无监督自适应分割；对于序列图像，则可以利用样本图像训练字典，并利用训练字典完成序列图像的分割.通过对SBD数据库的大脑MRI序列图像进行分割实验，结果表明,该算法有较好的分割精度，且能够保持序列医学图像分割的准确性和一致性.

关键词: 聚类, 字典学习, 稀疏表示, 医学图像分割

Abstract: To improve the segmentation performance of medical images, dictionary learning was combined with clustering algorithm, and a medical image segmentation algorithm was proposed taking dictionaries as clustering centers and using sparse representation to cluster for segmentation. For a single medical image, unsupervised adaptive segmentation can be achieved by alternately iterating the sparse coding and updating the dictionary to convergence. For the medical image sequence, the sample images can be picked to obtain the trained dictionaries to complete the segmentation of the image sequence. According to the segmentation results of the synthetic images and the magnetic resonance images of the human brain from SBD database, it can be perceived that the proposed algorithm could not only improve segmentation accuracy, but also maintain the accuracy and consistency of sequential medical image segmentation.

Key words: clustering, dictionary learning, sparse representation, medical image segmentation

中图分类号:

Q-334
TP751

张滨凯，王翔，郑津津. 结合字典学习和稀疏聚类的医学图像分割算法[J]. 中国科学技术大学学报, 2019, 49(10): 791-796.

ZHANG Binkai, WANG Xiang, ZHENG Jinjin. Medical image segmentation algorithm based on dictionary learning and sparse clustering[J]. Journal of University of Science and Technology of China, 2019, 49(10): 791-796.

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结合字典学习和稀疏聚类的医学图像分割算法

Medical image segmentation algorithm based on dictionary learning and sparse clustering

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