A novel technique to incorporate structural prior information into multi-modal tomographic reconstruction
A novel technique to incorporate structural prior information into multi-modal tomographic reconstruction
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DOI：
10.1088/0266-5611/30/6/065004
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发表时间：
2014-06-01
期刊：
影响因子：
2.1
通讯作者：
Arridge, Simon R.
中科院分区：
文献类型：
--
作者：
Kazantsev, Daniil;Ourselin, Sebastien;Arridge, Simon R.
断层扫描中的多模态成像技术得到了迅速扩展。在生物医学成像中，现在定期使用单光子发射计算机断层扫描 (SPECT) 和 X 射线计算机断层扫描 (CT)，或同时使用正电子发射断层扫描和磁共振成像 (MRI) 对患者进行成像。在材料的无损检测中，中子 CT (NCT) 和 X 射线 CT 被广泛应用于研究材料的内部结构或跟踪物理过程的动态。组合模式的潜在好处引起了人们对迭代重建算法的兴趣增加，这些算法可以同时利用来自多种成像模式的数据。我们在迭代重建中提出了一个新的正则化项，使来自一种成像模态的信息能够用作结构先验，以提高第二种模态的分辨率。正则化项基于改进的各向异性张量扩散滤波器，该滤波器具有形状自适应平滑特性。通过考虑两个共同配准图像的法向和切向矢量场的基本方向，扩散通量根据图像特征自适应地旋转和缩放。图像可以具有不同的灰度值和不同的空间分辨率。所提出的方法特别擅长隔离图像中的定向特征，这对于医学和材料科学应用非常重要。通过增强边缘，它可以轻松识别和体积分数测量，从而帮助用于量化的分割算法。该方法在标准去噪和去模糊图像恢复问题上进行了测试，然后应用于 2D 和 3D 重建问题；从而突出了算法的能力。使用 SPECT 与 MRI 共同配准的合成数据以及与 X 射线 CT 共同配准的真实 NCT 数据，我们展示了如何在一系列成像模式中使用该方法。
There has been a rapid expansion of multi-modal imaging techniques in tomography. In biomedical imaging, patients are now regularly imaged using both single photon emission computed tomography (SPECT) and x-ray computed tomography (CT), or using both positron emission tomography and magnetic resonance imaging (MRI). In non-destructive testing of materials both neutron CT (NCT) and x-ray CT are widely applied to investigate the inner structure of material or track the dynamics of physical processes. The potential benefits from combining modalities has led to increased interest in iterative reconstruction algorithms that can utilize the data from more than one imaging mode simultaneously. We present a new regularization term in iterative reconstruction that enables information from one imaging modality to be used as a structural prior to improve resolution of the second modality. The regularization term is based on a modified anisotropic tensor diffusion filter, that has shape-adapted smoothing properties. By considering the underlying orientations of normal and tangential vector fields for two co-registered images, the diffusion flux is rotated and scaled adaptively to image features. The images can have different greyscale values and different spatial resolutions. The proposed approach is particularly good at isolating oriented features in images which are important for medical and materials science applications. By enhancing the edges it enables both easy identification and volume fraction measurements aiding segmentation algorithms used for quantification. The approach is tested on a standard denoising and deblurring image recovery problem, and then applied to 2D and 3D reconstruction problems; thereby highlighting the capabilities of the algorithm. Using synthetic data from SPECT co-registered with MRI, and real NCT data co-registered with x-ray CT, we show how the method can be used across a range of imaging modalities.