Blind blur assessment of MRI images using parallel multiscale difference of Gaussian filters.
Blind blur assessment of MRI images using parallel multiscale difference of Gaussian filters.
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DOI：
10.1186/s12938-018-0514-4
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发表时间：
2018-06-13
影响因子：
3.9
通讯作者：
Wendel-Mitoraj KE
中科院分区：
文献类型：
--
作者：
Osadebey ME;Pedersen M;Arnold DL;Wendel-Mitoraj KE
Rician噪声、偏置场和模糊是在采集期间降低MRI图像质量的常见失真。与Rician噪声和偏置场相比，模糊是独特的，因为它可以被引入到采集阶段之外的图像中，例如采集后处理和病理状况的表现。大多数当前的模糊评估算法是在诸如电视、视频和移动的电器之类的消费电子产品上设计和验证的。专用于医学图像的少数算法要么需要参考图像，要么采用手动方法。由于这些原因，难以比较来自不同图像和具有不同内容的图像的质量测量。此外，它们将不适用于处理大量图像的环境。在本报告中，我们针对不同类型的MRI图像和包括自动化环境在内的不同应用提出了一种新的盲模糊评估方法。生成测试图像的两个副本。边缘图的提取是通过将测试图像的每个副本分别与两个并行的高斯差分滤波器进行卷积来实现的。在多尺度表示开始时，滤波器的初始输出相等。在多尺度表示的后续尺度中，每个滤波器在相同的固定高斯尺度范围内被调谐到不同的操作参数。这些滤波器被称为低能量滤波器和高能量滤波器，这是基于它们在多尺度表示的范围内连续衰减和突出边缘的特性。质量分数是从过滤器最终输出的边缘图的归一化平均值之间的距离预测的。所提出的方法进行了评估心脏和大脑MRI图像。性能评价表明，质量指标与人的感知有很好的相关性，将适合于在常规临床实践和临床研究中的应用。
Rician noise, bias fields and blur are the common distortions that degrade MRI images during acquisition. Blur is unique in comparison to Rician noise and bias fields because it can be introduced into an image beyond the acquisition stage such as postacquisition processing and the manifestation of pathological conditions. Most current blur assessment algorithms are designed and validated on consumer electronics such as television, video and mobile appliances. The few algorithms dedicated to medical images either requires a reference image or incorporate manual approach. For these reasons it is difficult to compare quality measures from different images and images with different contents. Furthermore, they will not be suitable in environments where large volumes of images are processed. In this report we propose a new blind blur assessment method for different types of MRI images and for different applications including automated environments. Two copies of the test image are generated. Edge map is extracted by separately convolving each copy of the test image with two parallel difference of Gaussian filters. At the start of the multiscale representation, the initial output of the filters are equal. In subsequent scales of the multiscale representation, each filter is tuned to different operating parameters over the same fixed range of Gaussian scales. The filters are termed low and high energy filters based on their characteristics to successively attenuate and highlight edges over the range of multiscale representation. Quality score is predicted from the distance between the normalized mean of the edge maps at the final output of the filters. The proposed method was evaluated on cardiac and brain MRI images. Performance evaluation shows that the quality index has very good correlation with human perception and will be suitable for application in routine clinical practice and clinical research.
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DOI：
10.1186/1532-429x-15-55
发表时间：
2013-06-20
期刊：
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
影响因子：
--
作者：
Klinke V;Muzzarelli S;Lauriers N;Locca D;Vincenti G;Monney P;Lu C;Nothnagel D;Pilz G;Lombardi M;van Rossum AC;Wagner A;Bruder O;Mahrholdt H;Schwitter J
通讯作者：
Schwitter J
使用基于混合水平集的活动轮廓邻域模型从脑 MRI 体积中提取大脑
影响因子：
3.9
作者：
Jiang S;Zhang W;Wang Y;Chen Z
通讯作者：
Chen Z
影响因子：
1.1
作者：
Ciancio, A.;da Costa, A. L. N. T.;Obrador, P.
通讯作者：
Obrador, P.
影响因子：
3.9
作者：
Gusso, Silmara;Salvador, Carlo;Nielsen, Poul
通讯作者：
Nielsen, Poul
DOI：
10.1016/j.jvcir.2017.11.017
发表时间：
2018-01-01
影响因子：
2.6
作者：
Gvozden, Goran;Grgic, Sonja;Grgic, Mislav
通讯作者：
Grgic, Mislav