Spectral-spatial filtering for efficient multi-material decomposition in x-ray CT

项目总结/摘要 计算机断层扫描（CT）是一种非常重要的诊断工具，每年约有8000万次扫描 其中超过一半的扫描使用外源性造影剂来增强各种病变的可视化， 以提供功能信息。光谱CT使用不同光谱通道的数据采集来分离 单个材料，并提供特定造影剂的浓度图。造影剂显影- 金属是一个活跃的研究领域，有许多新的化合物正在研究中，包括金，铋，钆， 基于锂、氙和镧系元素的造影剂。在单个AC中同时进行多个药剂的成像- 采集对于多相研究和多系统（例如，血管造影术/呼吸系统或 造影/胃肠道）研究。类似地，即使单独估计代理，提供操作的灵活性， 在剂量利用和/或提高低浓度可见度方面， 限制.然而，当前的谱CT系统在其对多种造影剂成像的能力方面受到限制， 由于可用频谱信道的数量有限（例如，两个双能源系统）或由于其限制， 在成形X射线光谱方面有限的灵活性（例如，使用一个或在双源系统中使用两个X射线滤波器）。 我们提出了一种新的和相对简单的硬件修改适用于目前的诊断CT， 以及能够实现或增强材料分解能力的临床前光谱CT原型， 分别这个概念借用了彩色光学成像中使用的一个想法，其中光谱信息是en- 使用平铺滤波器进行空间编码。对于X射线成像，这些滤波器可以由具有k边缘的材料组成， 诊断范围来影响特定的光谱形状。使用这些滤波器的数据采集将是稀疏的 每个光谱通道。通常，这将对传统的重建和物质重建提出挑战。 然而，基于模型的材料分解（MBMD）和压缩传感允许直接 根据投影测量估计材料浓度，从而实现这种独特的数据采集。 拟议的硬件和软件联合研究工作有以下具体目标。目标1：表征 并设计光谱空间滤波器。我们将开发光谱空间滤波器的模型，以实现仿真， MBMD重建和优化滤波器设计。目标2：构造谱空间滤波器并实现 CT测试台中稀疏数据采集。我们将开发用于制造和集成特定的方法， 在CT测试台上进行测试。目的3：评价频谱-空间滤波CT在物理材料识别中的作用。 合成实验新型光谱CT设计相对于当前方法的性能 将进行评估，包括低剂量和低浓度造影剂限值。圆满完成这些目标 将建立频谱空间滤波方法的可行性，作为对两种标准诊断的修改， tic CT（通过相对简单的修改实现光谱成像）和现有的光谱CT原型 （提供额外的光谱整形能力，用于更好的剂量利用和更低的浓度限制）。

PROJECT SUMMARY / ABSTRACT Computed tomography (CT) scans is an extremely important diagnostic tool with ~80 million scans per year with over half of those scans using exogenous contrast agents to enhance visualization of various lesions and to provide functional information. Spectral CT uses data acquisition with different spectral channels to separate individual materials and to provide concentration maps of particular contrast agents. Contrast agent develop- ment is an active research area with many new compounds under investigation including gold, bismuth, gado- linium, xenon, and lanthanide-based contrast agents. Imaging of multiple agents simultaneously in a single ac- quisition has distinct advantages for multiphasic studies and multisystem (e.g., angiography/respiratory or an- giography/gastrointestinal) studies. Similarly, even if agents are estimated individually, flexibility to provide op- timal spectra for those agents is desirable in terms of dose utilization and/or raising low concentration visibility limits. However, current spectral CT systems are limited in their ability to image multiple contrast agents either due to the limited number of spectral channels available (e.g., two in dual-energy systems) or due to their lim- ited flexibility in shaping the x-ray spectrum (e.g., using one, or in dual-source system two x-ray filters). We propose a novel and relatively simple hardware modification applicable to both current diagnostic CT as well preclinical spectral CT prototypes that can either enable or enhance material decomposition capabilities, respectively. The concept borrows from an idea used in color optical imaging where spectral information is en- coded spatially using tiled filters. For x-ray imaging, these filters can be comprised of materials with k-edges in the diagnostic range to effect specific spectral shapes. Data acquisitions using these filters will be sparse in each spectral channel. Ordinarily this would present a challenge for traditional reconstruction and material de- composition; however, model-based material decomposition (MBMD) and compressed sensing allow for direct estimation of material concentration from the projection measurements enabling this unique data acquisition. The proposed joint hardware and software research effort has the following specific aims. Aim 1: Characterize and design spectral-spatial filters. We will develop models for spectral-spatial filters to enable simulation, MBMD reconstruction, and optimized filter design. Aim 2: Construct spectral-spatial filters and implement sparse data acquisition in a CT test bench. We will develop methods for fabrication and integration of spec- tral-spatial filters into a CT test bench. Aim 3: Evaluate spectral-spatial filtered CT in physical material de- composition experiments. Performance of the novel spectral CT designs relative to current methodologies will be assessed including low-dose and low-concentration contrast limits. Successful completion of these aims will establish the feasibility of the spectral-spatial filtering approach as a modification to both standard diagnos- tic CT (enabling spectral imaging with a relatively simple modification) and to existing spectral CT prototype (providing additional spectral shaping capabilities for better dose utilization and lower concentration limits).