Reducing noise of mammographic LCD Displays

描述（由申请人提供）：SBIR第一期提案解决了由于有源矩阵液晶显示器（AMLCD）噪声导致的图像质量下降的问题，AMLCD越来越多地被用作临床医学的主要诊断软拷贝显示器，特别是乳房x光检查。本提案的主要目标是探索LCD噪声的特性，并开发一种可靠且易于实现的方法来评估和降低它。LCD空间噪声被定义为LCD像素之间和像素内部的微小但可检测和平稳的亮度差异。量化噪声是由显示的量化（位深）不足引起的。我们将使用高质量的CCD（电荷耦合器件）相机进行物理评估。本文将对500万像素EIZO LCD中央部分的空间噪声进行评估。通过信号建模和图像处理，分析和估计相机图像的空间噪声特性。一种基于误差扩散的算法来补偿LCD空间噪声和量化噪声，并在图像显示前对其进行处理。我们将使用西门子公司研究中心开发的视觉图像质量度量（VIQM）模型和信道化模型观察者来预测噪声补偿对人类检测性能的影响。还将进行一项人类观察者研究，以验证模型的预测，并评估降噪对实际诊断性能的影响。本文的研究重点是乳房x线摄影LCD显示噪声的降低。噪声降低的显示器可以更容易或更早地在全场数字乳房x光检查（FFDM）中发现疾病。如果能在早期阶段发现乳腺癌，治疗成功的几率就会更高。设计并实现了一种基于误差扩散的显示降噪方案。西门子开发的人类视觉模型将用于定量评估该方法的性能。我们将使用ffdm的部分进行一项人体观察员试验研究，以评估降噪方案对诊断性能的影响。

DESCRIPTION (provided by applicant): This SBIR Phase I proposal addresses the problem of image quality degradation due to noise of Active Matrix Liquid Crystal Displays (AMLCD), which are increasingly used as primary diagnostic softcopy display in clinical medicine, especially for mammography. The primary goal of this proposal is to explore the properties of LCD noise and to develop a reliable and easy to implement method to evaluate and reduce it. LCD spatial noise is defined as small but detectable and stationary inter- and intra- LCD pixel luminance differences. Quantization noise results from insufficient quantization (bit-depth) of the display. We will use a high quality CCD (charge coupled device) camera for physical evaluation. The spatial noise of the central portion of a 5-Mpixel EIZO LCD will be evaluated. Spatial noise properties will be analyzed and estimated from the camera images via signal modeling and image processing. An error diffusion based algorithm to compensate for the LCD spatial noise as well as the quantization noise will be used to process images before they are displayed. We will use the Visual Image Quality Metric (VIQM) model developed at Siemens Corporate Research with channelized model observers to predict the effects of noise compensation on human detection performance. A human observer study will also be conducted to verify the predictions of the model and evaluate the impact of noise reduction on actual diagnostic performance. The proposed research focuses on the reduction of mammographic LCD display noise. Displays with reduced noise could lead to easier or earlier detection of disease in Full Field Digital Mammograms (FFDM). If the detection of breast cancer can be accomplished at an earlier stage, there will be a higher chance for successful therapy. An error-diffusion-based display noise reduction scheme will be designed and implemented. A human visual model developed at Siemens will be used to quantitatively evaluate the performance of the approach. A pilot human observer study using sections of FFDMs will be conducted to evaluate the impact of noise reduction scheme on diagnostic performance.