Real-time, Automatic Image Quality Assessment for Digital Fundus Camera

描述（由申请人提供）：实时图像质量是许多医疗保健环境中的关键要求。此外，非实时应用，例如研究和药物研究，由于不可用（不可交易）的视网膜图像而遭受数据丢失。一些已发表的报告表明，由于图像质量，10%至15%的图像被从研究中拒绝。随着视网膜摄影术向临床中训练较少的个人的过渡，图像质量可能受到影响，除非存在实时评估图像质量并向摄影师提供用于校正照片获取中的技术错误的建议的手段。在第一阶段，该项目展示了一种方法，用于实时评估来自基金照相机的数字图像，并向操作员提供关于图像质量的反馈。我们表明，可以在质量差的图像中识别问题的根源，并为摄影师提供纠正措施。通过向摄影师提供实时反馈，可以采取纠正措施，消除数据丢失或给患者带来的不便。我们成功地将我们的方法应用于散瞳和非散瞳成像条件下来自四种不同相机的2，000多张图像。我们证明了该技术在未压缩和压缩（JPEG）图像上同样有效。在第二阶段，我们将进一步验证具有不同特征的其他数据的方法，以证明其广泛的适用性。由于我们的方法使用的参数，建议由人类的感知质量，我们已经表明，该算法可以适应各种图像质量协议。真实的实时视网膜图像质量方法是基于由分级者或眼科医生分配的图像质量分数。在商业上，眼底照相机的许多制造商对实时图像质量评估系统感兴趣。我们的方法将被证明是可扩展到任何数字图像。我们将把算法集成到两个商业相机（Topcon和佳能）的图像采集软件中。我们的方法也将是非常有价值的筛选中心，质量差的图像可以立即报告给当地或远程摄影师。商业上将有三个产品：一，我们将软件直接集成到眼底相机的图像采集软件。第二，我们将生产一个独立的图像质量软件包，供个人在诊所或研究中使用。第三，我们将整合我们的软件，并使其适应特定的协议，如威斯康星州眼底照片阅读中心。2 公共卫生相关性：视网膜图像的实时质量评估对于确保及时检测和诊断视网膜疾病至关重要。实时意味着当患者仍然在眼底相机处时识别质量差的图像。在定期对受试者进行成像的大型研究中，当场识别质量差的图像将避免需要将受试者带回重新成像或丢失来自研究的统计学关键数据点。远程眼科需要相同的实时图像质量评估，以确保患者的优质医疗保健。1

DESCRIPTION (provided by applicant): Real-time image quality is a critical requirement in a number of healthcare environments. Additionally, non-real-time applications, such as research and drug studies suffer loss of data due to unusable (untradeable) retinal images. Several published reports indicate that from 10% to 15% of images are rejected from studies due to image quality. With the transition of retinal photography to lesser trained individuals in clinics, image quality may suffer unless there is a means to assess the quality of an image in real-time and give the photographer recommendations for correcting technical errors in the acquisition of the photograph. In Phase I, this project demonstrated a methodology for evaluating a digital image from a funds camera in real-time and giving the operator feedback as to the quality of the image. We showed that it is possible to identify the source of the problem in poor quality images and give the photographer corrective actions. By providing real-time feedback to the photographer, corrective actions can be taken and loss of data or inconvenience to the patient eliminated. We successfully applied our methodology to over 2,000 images from four different cameras under mydriatic and non-mydriatic imaging conditions. We showed that the technique was equally effective on uncompressed and compressed (JPEG) images. In Phase II, we will validate the methodology further on additional data with different characteristics to demonstrate its broad applicability. Because our methodology uses parameters that are suggested by human perception qualities, we have shown that the algorithm can adapt to a variety of image quality protocols. The real- time retinal image quality methodology is based on image quality scores assigned by graders or ophthalmologists. Commercially, a real-time image quality assessment system is of interest to many manufacturers of fundus cameras. Our methodology will be demonstrated to be scalable to any digital imagery. We will integrate the algorithm into the image acquisition software of two commercial cameras (Topcon and Canon). Our methodology will also be of great value to screening centers where poor quality images can be reported immediately to the local or remote photographer. Commercially there will be three products: One, we will integrate the software directly into fundus cameras' image acquisition software. Two, we will produce a stand-alone image quality software package for use by individuals in clinics or research. Three, we will integrate our software and adapt it to specific protocols, such as the Wisconsin Fundus Photo Reading Center. 2 PUBLIC HEALTH RELEVANCE: Real-time quality assessment of a retinal image is critical to ensure timely detection and diagnosis of retinal diseases. Real-time means identifying poor quality images while the patient is still at the fundus camera. In large studies, where subjects are imaged periodically, identifying poor quality images on the spot will obviate the need to bring subjects back for re-imaging or losing a statistically critical data point from the study. Tele-ophthalmology requires the same real-time image quality assessment to ensure quality healthcare for the patients. 1