• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Advanced Technologies for Signal and Image Processing >Histogram equalization-based techniques for contrast enhancement of MRI brain Glioma tumor images: Comparative study
【24h】

Histogram equalization-based techniques for contrast enhancement of MRI brain Glioma tumor images: Comparative study

机译：基于直方图均衡化的MRI脑胶质瘤肿瘤图像对比增强技术：比较研究

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In Magnetic Resonance Imaging (MRI), the poor images quality, particularly the artifacts inherent to this type of images as well as the low contrast between tissues and inter-individual variability, could make difficult the image analysis and affect the accuracy of clinical diagnosis. Therefore, the needs for image enhancement techniques arise to improve the relevant image contents through reducing the noise while preserving the actual details features. Various MRI images denoising techniques have been proposed in literature where each technique has its advantages and limitations. Among them, the Histogram modifications-based approaches arise as the most employed, by many researchers, for MRI contrast enhancement. This paper presents a comparative study of the most histogram-based techniques, mainly AHE, CLAHE, BPDHE and AIR-AHE techniques, dealing with denoising and contrast enhancement MRI images. Experimental study, using real-world databases, is performed based on evaluation of quality measurement metrics: absolute mean brightness error (AMBE), peak signal to noise ratio (PSNR) and Entropy. The studied histogram-based technique's advantages and limitations are also discussed.
机译：在磁共振成像（MRI）中，较差的图像质量，尤其是此类图像固有的伪影以及组织之间的对比度低以及个体间的差异性，可能会使图像分析变得困难，并影响临床诊断的准确性。因此，需要图像增强技术以通过在保持实际细节特征的同时减少噪声来改善相关图像内容。在文献中已经提出了各种MRI图像去噪技术，其中每种技术都有其优点和局限性。其中，基于直方图修改的方法是许多研究人员最常用于MRI对比增强的方法。本文介绍了对大多数基于直方图的技术（主要是AHE，CLAHE，BPDHE和AIR-AHE技术）进行的比较研究，这些技术处理MRI图像的降噪和对比度增强。实验研究使用现实世界的数据库，是基于对质量测量指标的评估而进行的：绝对平均亮度误差（AMBE），峰值信噪比（PSNR）和熵。还讨论了所研究的基于直方图的技术的优点和局限性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号