Translation: About one scheme of tomography

使用无配对图像翻译实现计算机断层扫描（CT）重建核的厂商间协调

Inter-vendor harmonization of Computed Tomography (CT) reconstruction kernels using unpaired image translation

针对CT重建核不一致影响定量测量且现有方法需配对数据的问题，本研究构建多路径循环GAN实现无配对跨厂商核协调，减少了肺气肿测量差异并明确相关影响因素。

Numerical comparative study between regularized Gauss-Newton and Conjugate-Gradient methods in the context of microwave tomography

The reconstruction of relative permittivity and conductivity in microwave tomography is carried out using regularized Gauss-Newton and Conjugate-Gradient iterative schemes. These two approaches are numerically tested and compared in terms of resolution, speed of convergence and robustness to noise. The numerical results show that for noiseless data, the regularized Gauss-Newton iterative scheme has a better resolution and a higher convergence rate, while the Conjugate-Gradient iterative scheme remains the fastest in terms of calculation time per iteration. For noisy data, both approaches give …

Feasibility of a markerless tracking system based on optical coherence tomography

Clinical tracking systems are popular but typically require specific tracking markers. During the last years, scanning speed of optical coherence tomography (OCT) has increased to A-scan rates above 1 MHz allowing to acquire volume scans of moving objects. Thorefore, we propose a markerless tracking system based on OCT to obtain small volumetric images including information of sub-surface structures at high spatio-temporal resolution. In contrast to conventional vision based approaches, this allows identifying natural landmarks even for smooth and homogeneous surfaces. We describe the optomech…

全身体图像到图像翻译用于医疗数字孪生中的虚拟扫描仪

Whole-Body Image-to-Image Translation for a Virtual Scanner in a Healthcare Digital Twin

本文提出了一种基于区域分割的GAN方法，用于全身体CT到PET的图像翻译，通过分割身体为四个区域并使用区域特定的GANs提升翻译精度，从而在医疗数字孪生中实现更准确的虚拟PET扫描。

High-Speed Markerless Tissue Motion Tracking Using Volumetric Optical Coherence Tomography Images

Modern optical coherence tomography (OCT) devices provide volumetric images with micrometer-scale spatial resolution and a temporal resolution beyond video rate. In this work, we analyze an OCT-based prototypical tracking system which processes 831 volumes per second, estimates translational motion, and automatically adjusts the field-of-view, which has a size of few millimeters, to follow a sample even along larger distances. The adjustment is realized by two galvo mirrors and a motorized reference arm, such that no mechanical movement of the scanning setup is necessary. Without requiring a m…

A joint reconstruction and lambda tomography regularization technique for energy-resolved X-ray imaging

Here we present new joint reconstruction and regularization techniques inspired by ideas in microlocal analysis and lambda tomography, for the simultaneous reconstruction of the attenuation coefficient and electron density from X-ray transmission (i.e., X-ray CT) and backscattered data (assumed to be primarily Compton scattered). To demonstrate our theory and reconstruction methods, we consider the "parallel line segment" acquisition geometry of Webber and Miller ("Compton scattering tomography in translational geometries." Inverse Problems 36, no. 2 (2020): 025007), which is motivated by syst…

Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation

We cast the problem of image denoising as a domain translation problem between high and low noise domains. By modifying the cycleGAN model, we are able to learn a mapping between these domains on unpaired retinal optical coherence tomography images. In quantitative measurements and a qualitative evaluation by ophthalmologists, we show how this approach outperforms other established methods. The results indicate that the network differentiates subtle changes in the level of noise in the image. Further investigation of the model's feature maps reveals that it has learned to distinguish retinal l…

CoShaRP: A Convex Program for Single-shot Tomographic Shape Sensing

We introduce single-shot X-ray tomography that aims to estimate the target image from a single cone-beam projection measurement. This linear inverse problem is extremely under-determined since the measurements are far fewer than the number of unknowns. Moreover, it is more challenging than conventional tomography where a sufficiently large number of projection angles forms the measurements, allowing for a simple inversion process. However, single-shot tomography becomes less severe if the target image is only composed of known shapes. Hence, the shape prior transforms a linear ill-posed image …

Target-Dependent Chemical Species Tomography with Hybrid Meshing of Sensing Regions

This paper develops a hybrid-size meshing scheme for target-dependent imaging in Chemical Species Tomography (CST). The traditional implementation of CST generally places the target field in the central region of laser sensing, the so-called Region of Interest (RoI), with uniform-size meshes. The centre of the RoI locates at the midpoint between the laser emitters and receivers, while the size of the RoI is empirically determined by the optical layout. A too small RoI cannot make the most use of laser beams, while a too large one leads to much severer rank deficiency in CST. To solve the above…

DensePANet：一种用于从稀疏数据重建光声层析成像图像的改进生成对抗网络

DensePANet: An improved generative adversarial network for photoacoustic tomography image reconstruction from sparse data

针对光声层析成像稀疏数据重建易产生伪影的问题，提出基于FD-UNet++生成器的端到端生成对抗网络DensePANet，在体内与模拟数据集上表现优于其他主流深度学习技术。