Development of a low-cost hardware accelerator for 3D image registration.

描述（由申请人提供）：我们的总体目标是开发一种新颖的计算解决方案，用于在1分钟内自动准确地配准（空间对齐）任何形态和任何解剖（刚性或可变形）的三维（3D）医学图像。这种能力目前还不存在。现有的图像配准解决方案精度和/或适用性有限，阻碍了广泛和常规的临床应用。在之前重要的学术研究的基础上，我们将在这个为期一年的STTR第一期项目中展示创建拟议技术的可行性。在演示可行性后，我们将创建一个功能齐全的原型}一个紧凑的，相对低成本（制造成本：约20,000美元）的硬件加速图像配准PC板}，以商业化为最终目标。图像配准是现代医学的一项基本需求，但这一需求尚未得到满足。这是融合具有互补信息的图像之前必要的第一步，或者可以减去不同时间拍摄的图像以量化解剖/生理变化。图像配准还有许多其他应用，包括在许多新兴的微创图像引导干预中对术前和术中图像进行配准。通过系统级仿真和性能表征（我们的两个具体目标），我们将在第一阶段创建拟议硬件加速器的软件仿真。我们将使用这个功能相同且速度相似的模拟器注册大脑，肺和腹部的现有图像，以在1分钟或更短的时间内显示准确的图像配准。达到这些性能里程碑将提供证据，证明这种临床可行的多用途计算解决方案是可以创建的，并将证明过渡到II期和继续资助。我们提出的低成本、超快、易于使用和准确的计算解决方案有望释放医学图像配准的全部潜力。项目健康相关性：结合2个或更多不同类型的医学图像，提供关于患者状况的更精确信息。比较不同时间拍摄的图像有助于监测疾病对治疗的反应。在任何一种情况下，图像配准（对齐）是至关重要的第一步。目前的图像配准方法速度慢、复杂、繁琐，实用性有限。我们建议开发适用于大多数器官和图像类型的自动、高速、三维配准能力。我们会先在第一期示范这项技术的可行性，然后再在第二期进行全面发展。｝

DESCRIPTION (provided by applicant): Our overall goal is to develop a novel computing solution for automatic and accurate registration (spatial alignment) of three-dimensional (3D) medical images of any modality and any anatomy (rigid or deformable) in 1 minute. Such capability currently does not exist. Existing image registration solutions have limited accuracy and/or limited applicability, preventing wide and routine clinical use. Building on significant prior academic research, we will demonstrate the feasibility of creating the proposed technology in this 1-year STTR Phase I project. After demonstrating feasibility, we will create a fully functional prototype}a compact, relatively low- cost (manufacturing cost: ~$20,000) PC board}of hardware-accelerated image registration, with commercialization as the ultimate goal. Image registration is a fundamental need in modern medicine}a need that remains unmet. It is the necessary first step before images with complementary information can be fused, or images taken at different times can be subtracted to quantify anatomic/physiologic changes. Image registration has numerous other applications, including the registration of pre- and intraoperative images in a host of emerging minimally invasive image-guided interventions. Through system-level simulation and performance characterization (our 2 specific aims), we will create a software simulation of the proposed hardware accelerator in Phase I. We will register existing images of the brain, lungs, and abdomen using this functionally identical and similar-speed simulator to show accurate image registration in 1 min or less. Meeting these performance milestones will provide evidence that this clinically viable and multipurpose computing solution can be created and will justify transitioning to Phase II and continued funding. Our proposed low-cost, ultrafast, easy-to-use, and accurate computing solution promises to unlock the full potential of medical image registration. PROJECT HEALTH RELEVANCE: Combining 2 or more medical images of different types gives more precise information on a patient's condition. Comparing images taken at different times helps monitor how a disease is responding to treatment. In either case, image registration (alignment) is the crucial first step. Current image registration methods are slow, complex, and tedious, with limited practical applicability. We propose developing automatic, high-speed, three-dimensional registration capabilities that are applicable to most organs and image types. We will demonstrate the feasibility of creating such a technology in Phase I before its full development planned for Phase II. }