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Modelling of Subjective Radiological Assessments with Objective Image Quality Measures of Brain and Body CT Images

机译:大脑和身体CT图像的客观图像质量度量对主观放射学评估建模

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In this work we determine how well the common objective image quality measures (Mean Squared Error (MSE), local MSE, Signal-to-Noise Ratio (SNR), Structural Similarity Index (SSIM), Visual Signal-to-Noise Ratio (VSNR) and Visual Information Fidelity (VIF)) predict subjective radiologists' assessments for brain and body computed tomography (CT) images. A subjective experiment was designed where radiologists were asked to rate the quality of compressed medical images in a setting similar to clinical. We propose a modified Receiver Operating Characteristic (ROC) analysis method for comparison of the image quality measures where the "ground truth" is considered to be given by subjective scores. The best performance was achieved by the SSIM index and VIF for brain and body CT images. The worst results were observed for VSNR. We have utilized a logistic curve model which can be used to predict the subjective assessments with an objective criteria. This is a practical tool that can be used to determine the quality of medical images.
机译:在这项工作中,我们确定常见的客观图像质量度量(均方误差(MSE),局部MSE,信噪比(SNR),结构相似性指数(SSIM),视觉信噪比(VSNR) )和视觉信息保真度(VIF)预测主观放射科医生对大脑和身体计算机断层扫描(CT)图像的评估。设计了一个主观实验,要求放射科医生在类似于临床的环境中对压缩医学图像的质量进行评分。我们提出了一种改进的接收器操作特征(ROC)分析方法,用于比较图像质量度量,其中“地面真相”被认为是由主观得分给出的。通过SSIM指数和VIF对大脑和身体CT图像可获得最佳性能。对于VSNR,观察到最差的结果。我们已经使用了逻辑曲线模型,该模型可用于预测具有客观标准的主观评估。这是可用于确定医学图像质量的实用工具。

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