Mazaheri Samaneh, Sulaiman Puteri Suhaiza, Wirza Rahmita, Dimon Mohd Zamrin, Khalid Fatimah, Moosavi Tayebi Rohollah
Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), 43400 Serdang, Selangor, Malaysia.
Cardiothoracic Unit, Surgical Cluster, Faculty of Medicine, 40450 Shah Alam, Selangor, Malaysia.
Comput Math Methods Med. 2015;2015:486532. doi: 10.1155/2015/486532. Epub 2015 May 18.
Medical image fusion is the procedure of combining several images from one or multiple imaging modalities. In spite of numerous attempts in direction of automation ventricle segmentation and tracking in echocardiography, due to low quality images with missing anatomical details or speckle noises and restricted field of view, this problem is a challenging task. This paper presents a fusion method which particularly intends to increase the segment-ability of echocardiography features such as endocardial and improving the image contrast. In addition, it tries to expand the field of view, decreasing impact of noise and artifacts and enhancing the signal to noise ratio of the echo images. The proposed algorithm weights the image information regarding an integration feature between all the overlapping images, by using a combination of principal component analysis and discrete wavelet transform. For evaluation, a comparison has been done between results of some well-known techniques and the proposed method. Also, different metrics are implemented to evaluate the performance of proposed algorithm. It has been concluded that the presented pixel-based method based on the integration of PCA and DWT has the best result for the segment-ability of cardiac ultrasound images and better performance in all metrics.
医学图像融合是将来自一种或多种成像模态的多幅图像进行合并的过程。尽管在超声心动图中朝着心室自动分割和跟踪方向进行了大量尝试，但由于图像质量低，存在解剖细节缺失或斑点噪声以及视野受限等问题，该问题仍是一项具有挑战性的任务。本文提出了一种融合方法，该方法特别旨在提高超声心动图特征（如心内膜）的可分割性并改善图像对比度。此外，它试图扩大视野，降低噪声和伪影的影响，并提高回波图像的信噪比。所提出的算法通过主成分分析和离散小波变换的组合，对所有重叠图像之间关于一个积分特征的图像信息进行加权。为了进行评估，已将一些知名技术的结果与所提出的方法进行了比较。此外，还采用了不同的指标来评估所提出算法的性能。得出的结论是，所提出的基于主成分分析和离散小波变换积分的基于像素的方法在心脏超声图像的可分割性方面具有最佳结果，并且在所有指标上都具有更好的性能。
