As cone-beam computed tomography (CBCT) has gained popularity rapidly in dental imaging applications in the past two decades, radiation dose in CBCT imaging remains a potential, health concern to the patients. It is a common practice in dental CBCT imaging that only a small volume of interest (VOI) containing the teeth of interest is illuminated, thus substantially lowering imaging radiation dose. However, this would yield data with severe truncations along both transverse and longitudinal directions. Although images within the VOI reconstructed from truncated data can be of some practical utility, they often are compromised significantly by truncation artifacts. In this work, we investigate optimization-based reconstruction algorithms for VOI image reconstruction from CBCT data of dental patients containing severe truncations. In an attempt to further reduce imaging dose, we also investigate optimization-based image reconstruction from severely truncated data collected at projection views substantially fewer than those used in clinical dental applications. Results of our study show that appropriately designed optimization-based reconstruction can yield VOI images with reduced truncation artifacts, and that, when reconstructing from only one half, or even one quarter, of clinical data, it can also produce VOI images comparable to that of clinical images.
Analytic-based algorithms such as the FDK algorithm is used currently for image reconstruction from
data acquired with prototypes of dedicated breast CT scanners. In general, analytic-based algorithms require
data collected at a large number (~500) of views. In current
breast-CT scans, imaging dose delivered to the
patient is about the same as that used in a typical two-view mammography exam. This highly limited total
imaging dose, when distributed over a large number of views in breast CT, can result in low-SNR data. There
exists a renewed interest in developing optimization-based (i.e., iterative) algorithms for image reconstruction
from low-SNR data and/or from sparse-view data collected at a reduced number of views. Results of recent
studies on optimization-based algorithms from CT data suggest that the algorithms may reconstruct images
of quality higher than than analytic-based algorithms from low-SNR data and/or from sparse-view data. In
this work, we investigated image reconstruction from low-SNR
patient-breast-CT data collected at a large
number (~500), as well as at reduced numbers, of views. The result of the study appears to indicate that
optimization-based reconstructions can yield breast-CT images from low-SNR data comparable to, or better
than, the corresponding FDK reconstructions.
Proc. SPIE. 7961, Medical Imaging 2011: Physics of Medical Imaging
KEYWORDS: CT reconstruction, Physics, Computer simulations, Medical imaging, Data acquisition, Computed tomography, Reconstruction algorithms, Image-guided intervention, Current controlled current source
Cone-beam computed tomography (CBCT) has been increasingly used during surgical procedures for providing accurate three-dimensional anatomical information for intra-operative navigation and verification. High-quality CBCT images are in general obtained through reconstruction from projection data acquired at hundreds of view angles, which is associated with a non-negligible amount of radiation exposure to the patient. In this work, we have applied a novel image-reconstruction algorithm, the adaptive-steepest-descent-POCS (ASD-POCS) algorithm, to reconstruct CBCT images from projection data at a significantly reduced number of view angles. Preliminary results from experimental studies involving both simulated data and real data show that images of comparable quality to those presently available in clinical image-guidance systems can be obtained by use of the ASD-POCS algorithm from a fraction of the projection data that are currently used. The result implies potential value of the proposed reconstruction technique for low-dose intra-operative CBCT imaging applications.
Micro-CT enables convenient visualization and quantitative analysis of small animals and biological tissue samples. However, high-quality volume images in general require acquisition of cone-beam projection data from hundres of view angles. This prolonged imaging process limits system throughput and may cause potential radiation damage to the imaged objects. It is therefore desirable to have a technique which can generate volume images with satisfactory quality, but from a smaller amount of projection data. On the other hand, many objects subject to the micro-CT scans have sparse spatial distribution, and this sparcity could be exploited and incorporated as prior knowledge in innovative design of algorithms that are capable of reconstructuring images from few-view projection data. In this work we applied a new iterative algorithm based upon constrained total-variation minimization to reconstructing images from as few as five projections. Preliminary results suggest that the algorithm can yield potentially useful images from substantially less projection data than required by existing algorithms. This has practical implications of reducing scanning time and minimizing radiation damage to the imaged objects.
In recent years, near-infrared (NIR) autofluorescence imaging has been explored as a novel technique for tissue evaluation and diagnosis. We present an NIR fluorescence imaging system optimized for the dermatologic clinical setting, with particular utility for the direct characterization of cutaneous melanins in vivo. A 785-nm diode laser is coupled into a ring light guide to uniformly illuminate the skin. A bandpass filter is used to purify the laser light for fluorescence excitation, while a long-pass filter is used to block the main laser wavelength but pass the spontaneous components for NIR reflectance imaging. A computer-controlled filter holder is used to switch these two filters to select between reflectance and fluorescence imaging modes. Both the reflectance and fluorescence photons are collected by an NIR-sensitive charge-coupled device (CCD) camera to form the respective images. Preliminary results show that cutaneous melanin in pigmented skin disorders emits higher NIR autofluorescence than surrounding normal tissue. This confirmed our previous findings from NIR fluorescence spectroscopy study of cutaneous melanins and provides a new approach to directly image the distributions of cutaneous melanins in the skin. In-vivo NIR autofluorescence images may be useful for clinical evaluation and diagnosis of pigmented skin lesions, including melanoma.
Some of the recently developed image reconstruction algorithms for cone-beam computed tomography (CBCT)
involve the computation of the finite Hilbert transform. We have previously studied noise property of the finite
Hilbert transform and observed that it can be used for potentially improving the image noise property within a region
of interest (ROI) in IGRT. Imaging radiation dose is one of the critical issues in IGRT, and in addition to existing dose-reduction
schemes by use of ROI imaging, it is possible to achieve further patient dose reduction through modulating
beam intensity so that a sub-ROI in the ROI be exposed by high flux of x-ray photons and the rest of the ROI be
exposed by low flux of them. In this work, we investigate the technique for obtaining sub-ROI images, which is
supposed to include the target under treatment, with high contrast-to-noise ratio (CNR) and the images within the rest
of the ROI with low CNR. Numerical studies have been conducted as a preliminary in this work.
Melanin is essentially a nonfluoresent material under ultra-violet (UV) and short wavelength visible light excitation. However, fluorescence emission from in vivo cutaneous melanin has recently been detected spectroscopically under near-infrared (NIR) excitation by our group. The objective of this study is to develop an in vivo NIR autofluorescence imaging system for direct observation and characterization of melanin distribution in human skin. In the imaging system, light coming from a 785 nm diode laser is coupled into a ring light guide to uniformly illuminate the skin surface. The fluorescence or reflectance light is collected by an NIR-sensitive CCD camera with and without long-pass filters. Both reflectance and autofluorescence images of nevi from three volunteers were obtained with exposure time of less than 1 second. In NIR autofluorescence images the pigmented areas showed higher fluorescence than adjacent normal skin, thus confirmed the previous spectroscopic results and demonstrated great promises for using NIR autofluorescence for evaluating pigmented skin lesions.