Shikui Yan

A New Highly Versatile Multimodality Small Animal Imaging Platform

A new, highly versatile multi-modality small animal imaging platform, the Siemens Inveon Multimodality (MM) scanner, has been developed. This platform supports any combination of X-ray micro-CT, single-photon computed tomography (SPECT) and positron emission tomography (PET) modalities on a single gantry. Each modality within the system is designed to be configured with a different level of imaging performance based on the needs of the application. From a single control workstation, the end-user has the ability to tune the system configuration for each modality in terms of resolution, field-of-view (FOV), sensitivity, etc., as needed for the target application. The scanner platform is ergonomically designed to allow efficient access to the animal and employs a unique cable management device to allow more effective use of physiologic monitoring and anesthesia systems within a user-accessible X-ray shielded cabinet. The motivation for this versatile platform design is to accommodate a wide range of multi-modality imaging applications from mouse to small primate, each with performance parameters that can be tuned as driven by the target anatomy or biological process being studied within the animal.

Automated Least-Squares Calibration of the Coregistration Parameters for a Micro PET-CT System

PET-CT coregistration parameters can be derived from PET and CT images of a four-point-source calibration phantom for a micro PET-CT scanner. An automated segmentation method has been developed, based on thresholding and application of constraints on the sizes of point sources in the images. After point sources are identified on PET and CT images, coregistration is performed using an analytic rigid-body registration algorithm which is based on singular value decomposition and minimization of the coregistration error. The coregistration parameters thus derived can then be applied to coregister other PET and CT images from the same system. Twenty PET-CT images of the calibration phantom at various locations and/or orientations were obtained on a Siemens Inveon® Multi-Modality scanner. We tested the use of from 1 to 10 data sets to derive the coregistration parameters, and found that the coregistration accuracy improves with increasing number of data sets until it stabilizes. Coregistration of PET-CT images with an accuracy of 0.33±0.11 mm has been achieved by this method on the Inveon Multi-Modality scanner.

Beam hardening correction using a conical water-equivalent phantom for preclinical micro-CT

Beam hardening artifacts are a common occurrence in x-ray CT images. X-ray sources typically produce polychromatic photons and their relative absorption is a strong function of their energy. Despite this fact, most reconstruction algorithms assume the attenuation coefficient of the subject being scanned is invariant with the energy of the incident photons, and the quality of the reconstructed images is reduced. A practical method of correction for those artifacts is to calibrate the acquired data to the expected projections of a known geometry. Generally this method requires scans of multiple phantoms varying in size to calculate the parameters of the calibration function. The selection of the phantom data for determining the parameters can also affect the performance of the method. This work proposes a beam hardening correction (BHC) scheme using a specially designed, conical phantom for preclinical micro-CT. The conical shape simplifies both the data acquisition and the calculation of the calibration function for different object sizes. A 3rd degree polynomial is chosen as the calibration function used to correct the CT projection data. Experiments conducted with the Siemens Inveon™ micro CT showed that the artifacts were greatly suppressed.

Beam hardening correction using an attenuation coefficient decomposition approach

In X-ray CT system, the X-ray source generates x-rays with a broad range of spectrum. When the polychromatic photons travel through a subject, the lower energy photons are attenuated more effectively than the higher energy ones. This causes different attenuation coefficient (AC) of the material with respect to different X-ray photon energy. The reconstruction algorithms assuming invariant A C will introduce beam hardening artifacts in the reconstructed images. One effective method to address this is to model the X-ray attenuation process during the reconstruction. Generally an objective function is derived and an iterative method is used to minimize the objective function. This can be very time-consuming, and meanwhile it is relatively more difficult to compute such iterative algorithms in parallel. This work introduces an approach that uses an intermediate step to reduce the beam hardening artifacts. Due to the independence between the computation for each projection, it has the advantage of being able to compute in parallel.

Automated least-squares calibration of the coregistration parameters for a micro PET-CT system

A previously developed method derives co-registration parameters from PET and CT images of a four-point-source calibration phantom by manually adjusting the offsets and orientation of the CT image to achieve alignment with the PET image in a graphic viewer. This manual process is tedious and can be inaccurate, especially when rotational offsets exist. An automated segmentation method has been developed, based on thresholding and application of constraints on the sizes of point sources in the images. After point sources are identified on PET and CT images, co-registration is performed using an analytic rigid-body registration algorithm which is based on singular value decomposition and minimization of the co-registration error. The co-registration parameters thus derived can then be applied to co-register other PET and CT images from the same system. Twenty PET-CT images of the calibration phantom at various locations and/or orientations were obtained on a Siemens Inveon® Multi-Modality scanner. We tested the use of from 1 to 10 data sets to derive the co-registration parameters, and found that the co-registration accuracy improves with increasing number of data sets until it stabilizes. Co-registration of PET-CT images with an accuracy of 0.33±0.11 mm has been achieved by this method on the Inveon Multi-Modality scanner.

A study on spiral cone beam scanning mode for preclinical micro-CT

In preclinical micro-CT, a circular scanning trajectory is widely used, and the Feldkamp algorithm is usually the standard reconstruction method to recover the images. This imaging mode has the advantages of fast reconstruction speed and good intra-slice resolution for images near the central plane. However, it shows cone-beam artifacts for images at relatively large cone angles. To address this problem, a spiral scanning trajectory is employed for the micro-CT. Spiral reconstruction algorithms were utilized to reconstruct the images and compared with the standard Feldkamp algorithm. The results show that the spiral approach delivers images with reduced cone beam artifacts.