Evaluation of computational endomicroscopy architectures for minimally-invasive optical biopsy
Evaluation of computational endomicroscopy architectures for minimally-invasive optical biopsy
复制标题
微创光学活检的计算内窥镜架构的评估
DOI：
10.1117/12.2253134
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Pierce, Mark C.
中科院分区：
文献类型：
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作者：
Dumas, John P.;Lodhi, Muhammad A.;Bajwa, Waheed U.;Pierce, Mark C.
我们正在研究压缩传感结构在内窥镜中的应用，其中组织访问所需的窄直径探针可能会限制可实现的空间分辨率。我们假设，压缩传感框架可以通过重建具有比纤维束中的纤维更多可分辨的点的图像来克服基于纤维束的内窥镜中的基本像素数量限制。搭建了一个实验测试平台，通过在光学系统内的共轭图像或傅里叶平面引入编码幅度掩模，对两种候选结构进行了评估和比较。台式平台由共同的照明和物体路径组成，每个压缩结构都有单独的成像臂。成像臂包含一个数字微镜装置(DMD)作为可重新编程的掩模，以及一个用于图像采集的CCD摄像机。其中一个臂将DMD定位在共轭像平面(“IP臂”)，而另一个臂将DMD定位在傅立叶平面(“FP臂”)。镜头被选择并放置在每个手臂内，以实现16的元素与像素比率(230,400个遮罩元素映射到14,400个相机像素上)。我们讨论了每个系统臂的数学模型，并概述了考虑系统非理想性的重要性。利用基于优化的压缩传感算法对1951年的美国空军分辨率目标进行重建，当模型中包含系统非理想情况时，对于两个系统臂产生的图像具有比双三次插值法更高的空间分辨率。此外，与通过傅立叶平面编码获得的图像相比，利用图像平面编码生成的图像表现出更高的空间分辨率，但更多的噪声。
We are investigating compressive sensing architectures for applications in endomicroscopy, where the narrow diameter probes required for tissue access can limit the achievable spatial resolution. We hypothesize that the compressive sensing framework can be used to overcome the fundamental pixel number limitation in fiber-bundle based endomicroscopy by reconstructing images with more resolvable points than fibers in the bundle. An experimental test platform was assembled to evaluate and compare two candidate architectures, based on introducing a coded amplitude mask at either a conjugate image or Fourier plane within the optical system. The benchtop platform consists of a common illumination and object path followed by separate imaging arms for each compressive architecture. The imaging arms contain a digital micromirror device (DMD) as a reprogrammable mask, with a CCD camera for image acquisition. One arm has the DMD positioned at a conjugate image plane (“IP arm”), while the other arm has the DMD positioned at a Fourier plane (“FP arm”). Lenses were selected and positioned within each arm to achieve an element-to-pixel ratio of 16 (230,400 mask elements mapped onto 14,400 camera pixels). We discuss our mathematical model for each system arm and outline the importance of accounting for system non-idealities. Reconstruction of a 1951 USAF resolution target using optimization-based compressive sensing algorithms produced images with higher spatial resolution than bicubic interpolation for both system arms when system non-idealities are included in the model. Furthermore, images generated with image plane coding appear to exhibit higher spatial resolution, but more noise, than images acquired through Fourier plane coding.