Cerenkov luminescence tomography (CLT) is a promising tool that enables three-dimensional noninvasive in vivo detection of radiopharmaceuticals. Conventionally, multispectral information and diffusion theory were introduced to achieve whole-body tomographic reconstruction. However, the diffusion theory inevitably causes systematic error in blue bands of the electromagnetic spectrum due to high-tissue absorption, and CL has a blue-weighted broad spectrum. Therefore, it is challenging to improve the accuracy of CLT. The performance of the n-order simplified spherical harmonics approximation (SPn) in different spectra is evaluated, and a multispectral hybrid CLT based on the combination of different SPn models is proposed to handle the Cerenkov photon transport problem in complex media. The in vivo xenograft experiment shows that this approach can effectively improve the quality and accuracy of the reconstructed light source. We believe that the new reconstruction method will advance the development of CLT for more in vivo imaging applications.
Optical Projection Tomography (OPT) is a 3-Dimentional (3D) imaging technique for small specimens between 1mm and 10mm in size. Due to its high resolution and whole-body imaging ability, OPT has been widely used for imaging of small specimens such as murine embryos, murine organs, zebra fish, and plant sections. During an OPT imaging experiment, the ring artifacts are very common which severely impact the image quality of OPT. A ring artifact is caused by a bad pixel on the camera, or impurities on surface of lens and index matching vessel. Here we term these noises as coherent noise because they stay in the same image region during an OPT experiment. Currently, there is still no effective method to remove coherent noises. To address this problem, we propose a novel method to suppress the coherent noises before 3D OPT reconstruction. Our method consists of two steps: 1) find bad pixel positions on a blank image without specimen by using threshold segmentation, then fix the bad pixels on the projection image by using average of their neighbor pixels, 2) remove remained coherent noises on the sinogram by using Variational Coherent noise Remover (VSNR) method. After the two steps, lots of method can be used to generate the tomographic slices from the modified sinograms. We apply our method to a mouse heart imaging with our home-made OPT system. The experimental results show that our method has a good suppression on coherent noise and greatly improves the image quality. The innovation of our method is that we remove coherent noise automatically from both projection image and sinogram and they complement each other.
Optical projection tomography (OPT) is a mesoscopic scale optical imaging technique for specimens between 1mm and 10mm. OPT has been proven to be immensely useful in a wide variety of biological applications, such as developmental biology and pathology, but its shortcomings in imaging specimens containing widely differing contrast elements are obvious. The longer exposure for high intensity tissues may lead to over saturation of other areas, whereas a relatively short exposure may cause similarity with surrounding background. In this paper, we propose an approach to make a trade-off between capturing weak signals and revealing more details for OPT imaging. This approach consists of three steps. Firstly, the specimens are merely scanned in 360 degrees above a normal exposure but non-overexposure to acquire the projection data. This reduces the photo bleaching and pre-registration computation compared with multiple different exposures in conventional high dynamic range (HDR) imaging method. Secondly, three virtual channels are produced for each projection image based on the histogram distribution to simulate the low, normal and high exposure images used in the traditional HDR technology in photography. Finally, each virtual channel is normalized to the full gray scale range and three channels are recombined into one image using weighting coefficients optimized by a standard eigen-decomposition method. After applying our approach on the projection data, filtered back projection (FBP) algorithm is carried out for 3-dimentional reconstruction. The neonatal wild-type mouse paw has been scanned to verify this approach. Results demonstrated the effectiveness of the proposed approach.
Optical projection tomography (OPT) is a mesoscopic scale optical imaging technique for specimens between 1mm and 10mm. Although OPT is widely used for in vivo and ex vivo imaging, its applications in high intensity tissues such as bone and thick samples are limited due to the strong absorption of the light. In contrast, X-ray micro-CT is suitable for high intensity tissue imaging but its contrast of soft tissue is poor. Therefore, imaging tools with both strong penetration and high contrast are in great demand. To address this issue, we develop a dual-modality system integrating both OPT and micro-CT. In this paper, this dual-modality system is applied to dynamic imaging of a clearing process of a mouse paw. The clearing process is essential in OPT when imaging thick or intensity tissues since it can make high intensity tissues optically transparent. In our experiment, we scan the mouse paw with our system – before, during and after optical clearing. Each time we scan CT first and then the OPT. After acquisition, 3-dimentional volumes of OPT and CT are reconstructed separately. Then we use a rigid image registration algorithm to register these volumes. Finally, the volumes are merged together. The experimental results show our bimodal system performs better than single OPT or CT system when processing tissues with both high intensity and soft parts.
Laser sheet microscopy is a widely used imaging technique for imaging the three-dimensional distribution of a fluorescence signal in fixed tissue or small organisms. In laser sheet microscopy, the stripe artifacts caused by high absorption or high scattering structures are very common, greatly affecting image quality. To solve this problem, we report here a two-step procedure which consists of continuously acquiring laser sheet images while vertically displacing the sample, and then using the variational stationary noise remover (VSNR) method to further reduce the remaining stripes. Images from a cleared murine colon acquired with a vertical scan are compared with common stitching procedures demonstrating that vertically scanned light sheet microscopy greatly improves the performance of current light sheet microscopy approaches without the need for complex changes to the imaging setup and allows imaging of elongated samples, extending the field of view in the vertical direction.