Optimized Compression for Telepathology Virtual Slides

描述（由申请人提供）：我们建议研究一种方法，通过使用基于有关人类视觉系统的属性和功能的信息的图像压缩方案来改进远程病理学图像（即虚拟幻灯片）的呈现，以进行准确的诊断。尽管图像压缩技术已经在许多远程病理学应用中进行了研究和评估，但我们认为，这一领域尚未进行彻底的研究，将最先进的压缩方法与视觉建模和观察者性能研究相结合，将压缩方案、显示和临床医生视为一个动态和集成的实体，而不是彼此独立运行的各个部分。通过这种方法，我们相信我们可以为特定的远程病理学应用定制图像压缩方案，从而实现：（1）更快地交付图像，而不会影响视觉质量、实用性或诊断准确性； (2) 始终一致的视觉质量，以及跨图像、患者和显示技术优化的可变压缩率； (3) 基于人类观察者模拟的自动、客观的图像质量控制。我们最重要的假设是，通过根据有关人类视觉系统的功能和限制的信息定制图像压缩方案和显示，可以改进远程病理学图像的呈现，以实现准确的诊断。一旦我们通过远程病理图像证实了这种方法的实用性，它就可以很容易地推广到使用数字彩色图像进行存储和转发传输的其他远程医疗应用，例如远程皮肤病学，以及实时视频远程医疗应用（例如远程精神病学）。我们假设，可以使用基于有关人类视觉系统的功能和限制的信息的图像压缩方案来改进远程病理学图像的呈现，以进行准确的诊断。我们提出了两个具体目标来检验这一假设。一个潜在的长期目标是证明视觉辨别模型（VDM）在预测观察者性能（即医学图像中病变的检测和/或辨别）方面的实用性，作为各种存储转发和实时视频远程医疗应用中的压缩函数。这一目标的实现将确保随着更多压缩方案的开发或将其应用于独特的成像应用，可以避免或显着缩小时间和人员密集型接收器操作特性（ROC）实验（评估诊断性能的通常首选方法），同时仍然评估给定压缩方案或压缩级别对诊断性能的影响。

DESCRIPTION (provided by applicant): We propose to investigate a method to improve the presentation of telepathology images (i.e., virtual slides) for accurate diagnoses by using image compression schemes based on information about the properties and capabilities of the human visual system. Although image compression techniques have been studied and evaluated for use in many telepathology applications, we believe that there has yet to be a thorough investigation in this area that combines state-of-the-art compression methods with vision modeling and observer performance studies that take into account the compression schemes, the display, and the clinician as a dynamic and integrated entity rather than individual parts that operate independently of one another. Through this approach we believe that we can tailor image compression schemes for specific telepathology applications thereby enabling: (1) faster delivery of images without compromising visual quality, utility or diagnostic accuracy; (2) consistently uniform visual quality with variable compression rates optimized across images, patients, and display technologies; and (3) automatic, objective image-quality control based on simulations of the human observer. Our overriding hypothesis is that it is possible to improve the presentation of telepathology images for accurate diagnoses by tailoring image compression schemes and displays that are based on information about the capabilities and limitations of the human visual system. Once we have confirmed the utility of this approach with telepathology images, it can easily be generalized to other telemedicine applications that use digital color images for store-and-forward transmission such as teledermatology, as well as real-time video telemedicine applications (e.g., telepsychiatry). We hypothesize that it is possible to improve the presentation of telepathology images for accurate diagnoses using image compression schemes that are based on information about the capabilities and limitations of the human visual system. We propose two specific aims to test this hypothesis. An underlying long-term goal is to demonstrate the utility of a visual discrimination model (VDM) for predicting observer performance (i.e., detection and/or discrimination of lesions in medical images) as a function of compression in a variety of both store-forward and real-time video telemedical applications. The achievement of this goal will ensure that as more compression schemes are developed or as they are applied to unique imaging applications, time and personnel intensive Receiver Operating Characteristic (ROC) experiments (the generally preferred method for evaluating diagnostic performance) can either be avoided or reduced significantly in scope while still assessing the effects of a given compression scheme or level of compression on diagnostic performance.