A novel image-domain-based cone-beam computed tomography enhancement algorithm

Kilo-voltage (kV) cone-beam computed tomography (CBCT) plays an important role in image-guided radiotherapy. However, due to a large cone-beam angle, scatter effects significantly degrade the CBCT image quality and limit its clinical application. The goal of this study is to develop an image enhancement algorithm to reduce the low-frequency CBCT image artifacts, which are also called the bias field. The proposed algorithm is based on the hypothesis that image intensities of different types of materials in CBCT images are approximately globally uniform (in other words, a piecewise property). A maximum a posteriori probability framework was developed to estimate the bias field contribution from a given CBCT image. The performance of the proposed CBCT image enhancement method was tested using phantoms and clinical CBCT images. Compared to the original CBCT images, the corrected images using the proposed method achieved a more uniform intensity distribution within each tissue type and significantly reduced cupping and shading artifacts. In a head and a pelvic case, the proposed method reduced the Hounsfield unit (HU) errors within the region of interest from 300 HU to less than 60 HU. In a chest case, the HU errors were reduced from 460 HU to less than 110 HU. The proposed CBCT image enhancement algorithm demonstrated a promising result by the reduction of the scatter-induced low-frequency image artifacts commonly encountered in kV CBCT imaging.     

X-ray scattering in single- and dual-source CT

For medical imaging applications, such as cardiac imaging, dual-source computed tomography (CT) improves the temporal resolution by the simultaneous use of two cone beams, which acquire twice as many projections as single-source CT does within the same time interval. Besides this advantage, a drawback of such a system is additional x-ray scatter originating from the extra (cross-illuminating) cone beam. In this work, a comparison with single-source CT images is performed under same-dose conditions for two different thorax phantoms, and for different cone beam angles corresponding to a coverage of 20, 40, 80, and 160 mm on the rotation axis (z coverage). As a general result, the HU-magnitude of scatter-induced streak and cupping artifacts scale almost proportional to the illuminated volume. In dual-source CT, cross scatter induces a further factor of almost 2 in the scaling of artifacts in comparison to single-source CT. For all examined systems, the scatter-induced noise reduces the contrast-to-noise ratio (CNR). In the case of an ideal scatter correction, the CNR is reduced even more, but contrast and CNR can be restored by an additional x-ray dose. With a 32-slice single-source CT (z overage of 20 mm) taken as a reference, a corresponding dual-source CT requires 7% more dose to maintain the same CNR. A CT system with a z coverage of 40, 80, and 160 mm requires 8%, 23%, and 54% more dose in a single-source configuration, respectively, and 20%, 47%, and 102% more dose in a dual-source configuration, respectively. In conclusion, a dual-source CT is comparable to a single-source CT with twice the z coverage concerning image degradation by scatter.     

The influence of antiscatter grids on soft-tissue detectability in cone-beam computed tomography with flat-panel detectors

The influence of antiscatter x-ray grids on image quality in cone-beam computed tomography (CT) is evaluated through broad experimental investigation for various anatomical sites (head and body), scatter conditions (scatter-to-primary ratio (SPR) ranging from approximately 10% to 150%), patient dose, and spatial resolution in three-dimensional reconstructions. Studies involved linear grids in combination with a flat-panel imager on a system for kilovoltage cone-beam CT imaging and guidance of radiation therapy. Grids were found to be effective in reducing x-ray scatter "cupping" artifacts, with heavier grids providing increased image uniformity. The system was highly robust against ring artifacts that might arise in CT reconstructions as a result of gridline shadows in the projection data. The influence of grids on soft-tissue detectability was evaluated quantitatively in terms of absolute contrast, voxel noise, and contrast-to-noise ratio (CNR) in cone-beam CT reconstructions of 16 cm "head" and 32 cm "body" cylindrical phantoms. Imaging performance was investigated qualitatively in observer preference tests based on patient images (pelvis, abdomen, and head-and-neck sites) acquired with and without antiscatter grids. The results suggest that although grids reduce scatter artifacts and improve subject contrast, there is little strong motivation for the use of grids in cone-beam CT in terms of CNR and overall image quality under most circumstances. The results highlight the tradeoffs in contrast and noise imparted by grids, showing improved image quality with grids only under specific conditions of high x-ray scatter (SPR> 100%), high imaging dose (Dcenter> 2 cGy), and low spatial resolution (voxel size > or = 1 mm).     

A simple, direct method for x-ray scatter estimation and correction in digital radiography and cone-beam CT

X-ray scatter poses a significant limitation to image quality in cone-beam CT (CBCT), resulting in contrast reduction, image artifacts, and lack of CT number accuracy. We report the performance of a simple scatter correction method in which scatter fluence is estimated directly in each projection from pixel values near the edge of the detector behind the collimator leaves. The algorithm operates on the simple assumption that signal in the collimator shadow is attributable to x-ray scatter, and the 2D scatter fluence is estimated by interpolating between pixel values measured along the top and bottom edges of the detector behind the collimator leaves. The resulting scatter fluence estimate is subtracted from each projection to yield an estimate of the primary-only images for CBCT reconstruction. Performance was investigated in phantom experiments on an experimental CBCT bench-top, and the effect on image quality was demonstrated in patient images (head, abdomen, and pelvis sites) obtained on a preclinical system for CBCT-guided radiation therapy. The algorithm provides significant reduction in scatter artifacts without compromise in contrast-to-noise ratio (CNR). For example, in a head phantom, cupping artifact was essentially eliminated, CT number accuracy was restored to within 3%, and CNR (breast-to-water) was improved by up to 50%. Similarly in a body phantom, cupping artifact was reduced by at least a factor of 2 without loss in CNR. Patient images demonstrate significantly increased uniformity, accuracy, and contrast, with an overall improvement in image quality in all sites investigated. Qualitative evaluation illustrates that soft-tissue structures that are otherwise undetectable are clearly delineated in scatter-corrected reconstructions. Since scatter is estimated directly in each projection, the algorithm is robust with respect to system geometry, patient size and heterogeneity, patient motion, etc. Operating without prior information, analytical modeling, or Monte Carlo, the technique is easily incorporated as a preprocessing step in CBCT reconstruction to provide significant scatter reduction.     

Streaking artifacts reduction in four-dimensional cone-beam computed tomography

Cone-beam computed tomography (CBCT) using an "on-board" x-ray imaging device integrated into a radiation therapy system has recently been made available for patient positioning, target localization, and adaptive treatment planning. One of the challenges for gantry mounted image-guided radiation therapy (IGRT) systems is the slow acquisition of projections for cone-beam CT (CBCT), which makes them sensitive to any patient motion during the scans. Aiming at motion artifact reduction, four-dimensional CBCT (4D CBCT) techniques have been introduced, where a surrogate for the target's motion profile is utilized to sort the cone-beam data by respiratory phase. However, due to the limited gantry rotation speed and limited readout speed of the on-board imager, fewer than 100 projections are available for the image reconstruction at each respiratory phase. Thus, severe undersampling streaking artifacts plague 4D CBCT images. In this paper, the authors propose a simple scheme to significantly reduce the streaking artifacts. In this method, a prior image is first reconstructed using all available projections without gating, in which static structures are well reconstructed while moving objects are blurred. The undersampling streaking artifacts from static structures are estimated from this prior image volume and then can be removed from the phase images using gated reconstruction. The proposed method was validated using numerical simulations, experimental phantom data, and patient data. The fidelity of stationary and moving objects is maintained, while large gains in streak artifact reduction are observed. Using this technique one can reconstruct 4D CBCT datasets using no more projections than are acquired in a 60 s scan. At the same time, a temporal gating window as narrow as 100 ms was utilized. Compared to the conventional 4D CBCT reconstruction, streaking artifacts were reduced by 60% to 70%.     

A general framework and review of scatter correction methods in x-ray cone-beam computerized tomography. Part 1: Scatter compensation approaches

Since scattered radiation in cone-beam volume CT implies severe degradation of CT images by quantification errors, artifacts, and noise increase, scatter suppression is one of the main issues related to image quality in CBCT imaging. The aim of this review is to structurize the variety of scatter suppression methods, to analyze the common structure, and to develop a general framework for scatter correction procedures. In general, scatter suppression combines hardware techniques of scatter rejection and software methods of scatter correction. The authors emphasize that scatter correction procedures consist of the main components scatter estimation (by measurement or mathematical modeling) and scatter compensation (deterministic or statistical methods). The framework comprises most scatter correction approaches and its validity also goes beyond transmission CT. Before the advent of cone-beam CT, a lot of papers on scatter correction approaches in x-ray radiography, mammography, emission tomography, and in Megavolt CT had been published. The opportunity to avail from research in those other fields of medical imaging has not yet been sufficiently exploited. Therefore additional references are included when ever it seems pertinent. Scatter estimation and scatter compensation are typically intertwined in iterative procedures. It makes sense to recognize iterative approaches in the light of the concept of self-consistency. The importance of incorporating scatter compensation approaches into a statistical framework for noise minimization has to be underscored. Signal and noise propagation analysis is presented. A main result is the preservation of differential-signal-to-noise-ratio (dSNR) in CT projection data by ideal scatter correction. The objective of scatter compensation methods is the restoration of quantitative accuracy and a balance between low-contrast restoration and noise reduction. In a synopsis section, the different deterministic and statistical methods are discussed with respect to their properties and applications. The current paper is focused on scatter compensation algorithms. The multitude of scatter estimation models will be dealt with in a separate paper.     

基于旋转准直器的锥形束CT散射矫正方法

针对锥形束CT（CBCT）图像质量受散射影响比较严重的情况,提出一种基于旋转准直器的CBCT散射矫正方法。该方法在射线源和模体之间放置一个圆形的旋转准直器,并通过准直器的旋转使透过准直器的射线不断沿轴向来回扫描,以获取整个容积图像的投影图像信息,然后利用投影图像的遮挡区域估计整幅图像的散射信息并将其从投影图像中去除,最后利用改进FDK算法重建图像。结果表明,与CBCT图像相比,散射矫正后的重建图像CBCT值的均方根误差从16.00%下降为1.18%,杯状伪影从14.005%下降为0.660%,峰值信噪比从16.959 4提高到31.450 0。CBCT图像质量得到明显提高。     

Correction of megavoltage cone-beam CT images for dose calculation in the head and neck region

Megavoltage cone-beam computed tomography (MVCBCT) imaging systems are now available for image-guided radiation therapy delivery and verification. In order to use the three-dimensional anatomical information for dose calculation, the MVCBCT image must provide accurate electron density. This work proposes a new method that has been developed to correct for the cupping and missing data artifacts seen on MVCBCT images of the head and neck region. It uses a conventional kilovoltage CT (kVCT) image as a reference for electron density and rigid registration with a MVCBCT image to obtain correction factors. Dose calculations performed on MVCBCT images corrected with the proposed method agree with calculations done on kVCT images within +/- 1% on phantoms. With patients images the agreement is within +/- 13% above the shoulders and +/- 5% below the shoulder line. This level of dose calculation accuracy allows the use of MVCBCT images for dose verification purposes.     

Prospects for quantitative computed tomography imaging in the presence of foreign metal bodies using statistical image reconstruction

X-ray computed tomography (CT) images of patients bearing metal intracavitary applicators or other metal foreign objects exhibit severe artifacts including streaks and aliasing. We have systematically evaluated via computer simulations the impact of scattered radiation, the polyenergetic spectrum, and measurement noise on the performance of three reconstruction algorithms: conventional filtered backprojection (FBP), deterministic iterative deblurring, and a new iterative algorithm, alternating minimization (AM), based on a CT detector model that includes noise, scatter, and polyenergetic spectra. Contrary to the dominant view of the literature, FBP streaking artifacts are due mostly to mismatches between FBP's simplified model of CT detector response and the physical process of signal acquisition. Artifacts on AM images are significantly mitigated as this algorithm substantially reduces detector-model mismatches. However, metal artifacts are reduced to acceptable levels only when prior knowledge of the metal object in the patient, including its pose, shape, and attenuation map, are used to constrain AM's iterations. AM image reconstruction, in combination with object-constrained CT to estimate the pose of metal objects in the patient, is a promising approach for effectively mitigating metal artifacts and making quantitative estimation of tissue attenuation coefficients a clinical possibility.     

High temporal resolution and streak-free four-dimensional cone-beam computed tomography

Cone-beam computed tomography (CBCT) has been clinically used to verify patient position and to localize the target of treatment in image-guided radiation therapy (IGRT). However, when the chest and the upper abdomen are scanned, respiratory-induced motion blurring limits the utility of CBCT. In order to mitigate this blurring, respiratory-gated CBCT, i.e. 4D CBCT, was introduced. In 4D CBCT, the cone-beam projection data sets acquired during a gantry rotation are sorted into several respiratory phases. In these gated reconstructions, the number of projections for each respiratory phase is significantly reduced. Consequently, undersampling streaking artifacts are present in the reconstructed images, and the image contrast resolution is also significantly compromised. In this paper, we present a new method to simultaneously achieve both high temporal resolution ( approximately 100 ms) and streaking artifact-free image volumes in 4D CBCT. The enabling technique is a newly proposed image reconstruction method, i.e. prior image constrained compressed sensing (PICCS), which enables accurate image reconstruction using vastly undersampled cone-beam projections and a fully sampled prior image. Using PICCS, a streak-free image can be reconstructed from 10-20 cone-beam projections while the signal-to-noise ratio is determined by a denoising feature of the selected objective function and by the prior image, which is reconstructed using all of the acquired cone-beam projections. This feature of PICCS breaks the connection between the temporal resolution and streaking artifacts' level in 4D CBCT. Numerical simulations and experimental phantom studies have been conducted to validate the method.     

On-board four-dimensional digital tomosynthesis: first experimental results

The purpose of this study is to propose four-dimensional digital tomosynthesis (4D-DTS) for on-board analysis of motion information in three dimensions. Images of a dynamic motion phantom were reconstructed using acquisition scan angles ranging from 20 degrees (DTS) to full 360 degrees cone-beam computed tomography (CBCT). Projection images were acquired using an on-board imager mounted on a clinical linear accelerator. Three-dimensional (3D) images of the moving target were reconstructed for various scan angles. 3D respiratory correlated phase images were also reconstructed. For phase-based image reconstructions, the trajectory of a radiopaque marker was tracked in projection space and used to retrospectively assign respiratory phases to projections. The projections were then sorted according phase and used to reconstruct motion correlated images. By using two sets of projections centered about anterior-posterior and lateral axes, this study demonstrates how phase resolved coronal and sagittal DTS images can be used to obtain 3D motion information. Motion artifacts in 4D-DTS phase images are compared with those present in four-dimensional CT (4DCT) images. Due to the nature of data acquisition for the two modalities, superior-inferior motion artifacts are suppressed to a greater extent in 4D-DTS images compared with 4DCT. Theoretical derivations and experimental results are presented to demonstrate how optimal selection of image acquisition parameters including the frequency of projection acquisition and the phase window depend on the respiratory period. Two methods for acquiring projections are discussed. Preliminary results indicate that 4D-DTS can be used to acquire valuable kinetic information of internal anatomy just prior to radiation treatment.     

The impact of tumor motion upon CT image integrity and target delineation

Accurate planning target volume delineation is vital to the success of conformal radiation techniques such as standard three-dimensional conformal radiotherapy and intensity modulated radiation therapy. With the exception of breath-hold schemes, all current approaches acquire images while the tumor is nonstationary and, as such, are subject to the presence of motion artifacts. In lung cancer sites where tumor mobility can be significant, the detrimental effect of these motion-induced distortions on image quality and subsequently target volume delineation cannot be ignored in the pursuit of improved treatment outcomes. To investigate the fundamental nature and functional dependence of computed tomography (CT) artifacts associated with lung tumor motion, and the implications for tumor delineation, a filtered backprojection algorithm was developed in MATLAB to generate transverse CT simulation images. In addition, a three-dimensional phantom capable of mimicking the essential motions of lung tumors was constructed for experimental verification. Results show that the spatial extent of a mobile object is distorted from its true shape and location and does not accurately reflect the volume occupied during the extent of motion captured. The presence of motion also negatively impacts image intensity (density) integrity rendering accurate volume delineation highly problematic and calling into question the use of such data in CT-based heterogeneity correction algorithms for dosimetric calculation.     

Region-of-interest image reconstruction in circular cone-beam microCT

Cone-beam microcomputed tomography (microCT) is one of the most popular choices for small animal imaging which is becoming an important tool for studying animal models with transplanted diseases. Region-of-interest (ROI) imaging techniques in CT, which can reconstruct an ROI image from the projection data set of the ROI, can be used not only for reducing imaging-radiation exposure to the subject and scatters to the detector but also for potentially increasing spatial resolution of the reconstructed images. Increasing spatial resolution in microCT images can facilitate improved accuracy in many assessment tasks. A method proposed previously for increasing CT image spatial resolution entails the exploitation of the geometric magnification in cone-beam CT. Due to finite detector size, however, this method can lead to data truncation for a large geometric magnification. The Feldkamp-Davis-Kress (FDK) algorithm yields images with artifacts when truncated data are used, whereas the recently developed backprojection filtration (BPF) algorithm is capable of reconstructing ROI images without truncation artifacts from truncated cone-beam data. We apply the BPF algorithm to reconstructing ROI images from truncated data of three different objects acquired by our circular cone-beam microCT system. Reconstructed images by use of the FDK and BPF algorithms from both truncated and nontruncated cone-beam data are compared. The results of the experimental studies demonstrate that, from certain truncated data, the BPF algorithm can reconstruct ROI images with quality comparable to that reconstructed from nontruncated data. In contrast, the FDK algorithm yields ROI images with truncation artifacts. Therefore, an implication of the studies is that, when truncated data are acquired with a configuration of a large geometric magnification, the BPF algorithm can be used for effective enhancement of the spatial resolution of a ROI image.     

Development and validation of MCNP4C-based Monte Carlo simulator for fan- and cone-beam x-ray CT

An x-ray computed tomography (CT) simulator based on the Monte Carlo N-particle radiation transport computer code (MCNP4C) was developed for simulation of both fan- and cone-beam CT scanners. A user-friendly interface running under Matlab 6.5.1 creates the scanner geometry at different views as MCNP4C's input file. The full simulation of x-ray tube, phantom and detectors with single-slice, multi-slice and flat detector configurations was considered. The simulator was validated through comparison with experimental measurements of different nonuniform phantoms with varying sizes on both a clinical and a small-animal CT scanner. There is good agreement between the simulated and measured projections and reconstructed images. Thereafter, the effects of bow-tie filter, phantom size and septa length on scatter distribution in fan-beam CT were studied in detail. The relative difference between detected total, primary and scatter photons for septa length varying between 0 and 95 mm is 11.2%, 1.9% and 84.1%, respectively, whereas the scatter-to-primary ratio decreases by 83.8%. The developed simulator is a powerful tool for evaluating the effect of physical, geometrical and other design parameters on scanner performance and image quality in addition to offering a versatile tool for investigating potential artefacts and correction schemes when using CT-based attenuation correction on dual-modality PET/CT units.     

Compensators for dose and scatter management in cone-beam computed tomography

The ability of compensators (e.g., bow-tie filters) designed for kV cone-beam computed tomography (CT) to reduce both scatter reaching the detector and dose to the patient is investigated. Scattered x rays reaching the detector are widely recognized as one of the most significant challenges to cone-beam CT imaging performance. With cone-beam CT gaining popularity as a method of guiding treatments in radiation therapy, any methods that have the potential to reduce the dose to patients and/or improve image quality should be investigated. Simple compensators with a design that could realistically be implemented on a cone-beam CT imaging system have been constructed to determine the magnitude of reduction of scatter and/or dose for various cone-beam CT imaging conditions. Depending on the situation, the compensators were shown to reduce x-ray scatter at the detector and dose to the patient by more than a factor of 2. Further optimization of the compensators is a possibility to achieve greater reductions in both scatter and dose.     

Calibration of megavoltage cone-beam CT for radiotherapy dose calculations: correction of cupping artifacts and conversion of CT numbers to electron density

Megavoltage cone-beam CT (MV CBCT) is used for three-dimensional imaging of the patient anatomy on the treatment table prior to or just after radiotherapy treatment. To use MV CBCT images for radiotherapy dose calculation purposes, reliable electron density (ED) distributions are needed. Patient scatter, beam hardening and softening effects result in cupping artifacts in MV CBCT images and distort the CT number to ED conversion. A method based on transmission images is presented to correct for these effects without using prior knowledge of the object's geometry. The scatter distribution originating from the patient is calculated with pencil beam scatter kernels that are fitted based on transmission measurements. The radiological thickness is extracted from the scatter subtracted transmission images and is then converted to the primary transmission used in the cone-beam reconstruction. These corrections are performed in an iterative manner, without using prior knowledge regarding the geometry and composition of the object. The method was tested using various homogeneous and inhomogeneous phantoms with varying shapes and compositions, including a phantom with different electron density inserts, phantoms with large density variations, and an anthropomorphic head phantom. For all phantoms, the cupping artifact was substantially removed from the images and a linear relation between the CT number and electron density was found. After correction the deviations in reconstructed ED from the true values were reduced from up to 0.30 ED units to 0.03 for the majority of the phantoms; the residual difference is equal to the amount of noise in the images. The ED distributions were evaluated in terms of absolute dose calculation accuracy for homogeneous cylinders of different size; errors decreased from 7% to below 1% in the center of the objects for the uncorrected and corrected images, respectively, and maximum differences were reduced from 17% to 2%, respectively. The presented method corrects the MV CBCT images for cupping artifacts and extracts reliable ED information of objects with varying geometries and composition, making these corrected MV CBCT images suitable for accurate dose calculation purposes.     

Prior image constrained compressed sensing (PICCS): a method to accurately reconstruct dynamic CT images from highly undersampled projection data sets

When the number of projections does not satisfy the Shannon/Nyquist sampling requirement, streaking artifacts are inevitable in x-ray computed tomography (CT) images reconstructed using filtered backprojection algorithms. In this letter, the spatial-temporal correlations in dynamic CT imaging have been exploited to sparsify dynamic CT image sequences and the newly proposed compressed sensing (CS) reconstruction method is applied to reconstruct the target image sequences. A prior image reconstructed from the union of interleaved dynamical data sets is utilized to constrain the CS image reconstruction for the individual time frames. This method is referred to as prior image constrained compressed sensing (PICCS). In vivo experimental animal studies were conducted to validate the PICCS algorithm, and the results indicate that PICCS enables accurate reconstruction of dynamic CT images using about 20 view angles, which corresponds to an under-sampling factor of 32. This undersampling factor implies a potential radiation dose reduction by a factor of 32 in myocardial CT perfusion imaging.     

Cardiac cone-beam CT volume reconstruction using ART

Modern computed tomography systems allow volume imaging of the heart. Up to now, approximately two-dimensional (2D) and 3D algorithms based on filtered backprojection are used for the reconstruction. These algorithms become more sensitive to artifacts when the cone angle of the x-ray beam increases as it is the current trend of computed tomography (CT) technology. In this paper, we investigate the potential of iterative reconstruction based on the algebraic reconstruction technique (ART) for helical cardiac cone-beam CT. Iterative reconstruction has the advantages that it takes the cone angle into account exactly and that it can be combined with retrospective cardiac gating fairly easily. We introduce a modified ART algorithm for cardiac CT reconstruction. We apply it to clinical cardiac data from a 16-slice CT scanner and compare the images to those obtained with a current analytical reconstruction method. In a second part, we investigate the potential of iterative reconstruction for a large area detector with 256 slices. For the clinical cases, iterative reconstruction produces excellent images of diagnostic quality. For the large area detector, iterative reconstruction produces images superior to analytical reconstruction in terms of cone-beam artifacts.     

A Bayesian-MAP Method Based on TV for CT Image Reconstruction from Sparse and Limited Data

Computed tomography(CT) plays an important role in the field of modern medical imaging. Reducing radiation exposure dose without significantly decreasing image's quality is always a crucial issue. Inspired by the outstanding performance of total variation(TV) technique in CT image reconstruction, a TV regularization based Bayesian-MAP(MAP-TV) is proposed to reconstruct the case of sparse view projection and limited angle range imaging. This method can suppress the streak artifacts and geometrical deformation while preserving image edges. We used ordered subset(OS) technique to accelerate the reconstruction speed. Numerical results show that MAP-TV is able to reconstruct a phantom with better visual performance and quantitative evaluation than classical FBP,MLEM and quadrate prior to MAP algorithms. The proposed algorithm can be generalized to cone-beam CT image reconstruction.     

Empirical cupping correction: a first-order raw data precorrection for cone-beam computed tomography

We propose an empirical cupping correction (ECC) algorithm to correct for CT cupping artifacts that are induced by nonlinearities in the projection data. The method is raw data based, empirical, and requires neither knowledge of the x-ray spectrum nor of the attenuation coefficients. It aims at linearizing the attenuation data using a precorrection function of polynomial form. The coefficients of the polynomial are determined once using a calibration scan of a homogeneous phantom. Computing the coefficients is done in image domain by fitting a series of basis images to a template image. The template image is obtained directly from the uncorrected phantom image and no assumptions on the phantom size or of its positioning are made. Raw data are precorrected by passing them through the once-determined polynomial. As an example we demonstrate how ECC can be used to perform water precorrection for an in vivo micro-CT scanner (TomoScope 30 s, VAMP GmbH, Erlangen, Germany). For this particular case, practical considerations regarding the definition of the template image are given. ECC strives to remove the cupping artifacts and to obtain well-calibrated CT values. Although ECC is a first-order correction and cannot compete with iterative higher-order beam hardening or scatter correction algorithms, our in vivo mouse images show a significant reduction of bone-induced artifacts as well. A combination of ECC with analytical techniques yielding a hybrid cupping correction method is possible and allows for channel-dependent correction functions.