Page 1

Scatter correction for cone-beam CT in radiation therapy

Lei Zhu,a?Yaoqin Xie,b?Jing Wang, and Lei Xing

Department of Radiation Oncology, Stanford University, Stanford, California 94305

?Received 3 September 2008; revised 17 March 2009; accepted for publication 8 April 2009;

published 18 May 2009?

Cone-beam CT ?CBCT? is being increasingly used in modern radiation therapy for patient setup and

adaptive replanning. However, due to the large volume of x-ray illumination, scatter becomes a

rather serious problem and is considered as one of the fundamental limitations of CBCT image

quality. Many scatter correction algorithms have been proposed in literature, while a standard

practical solution still remains elusive. In radiation therapy, the same patient is scanned repetitively

during a course of treatment, a natural question to ask is whether one can obtain the scatter

distribution on the first day of treatment and then use the data for scatter correction in the subse-

quent scans on different days. To realize this scatter removal scheme, two technical pieces must be

in place: ?i? A strategy to obtain the scatter distribution in on-board CBCT imaging and ?ii? a

method to spatially match a prior scatter distribution with the on-treatment CBCT projection data

for scatter subtraction. In this work, simple solutions to the two problems are provided. A partially

blocked CBCT is used to extract the scatter distribution. The x-ray beam blocker has a strip pattern,

such that partial volume can still be accurately reconstructed and the whole-field scatter distribution

can be estimated from the detected signals in the shadow regions using interpolation/extrapolation.

In the subsequent scans, the patient transformation is determined using a rigid registration of the

conventional CBCT and the prior partial CBCT. From the derived patient transformation, the

measured scatter is then modified to adapt the new on-treatment patient geometry for scatter cor-

rection. The proposed method is evaluated using physical experiments on a clinical CBCT system.

On the Catphan©600 phantom, the errors in Hounsfield unit ?HU? in the selected regions of interest

are reduced from about 350 to below 50 HU; on an anthropomorphic phantom, the error is reduced

from 15.7% to 5.4%. The proposed method is attractive in applications where a high CBCT image

quality is critical, for example, dose calculation in adaptive radiation therapy. © 2009 American

Association of Physicists in Medicine. ?DOI: 10.1118/1.3130047?

Key words: scatter correction, radiation therapy, cone-beam CT, adaptive radiation therapy

I. INTRODUCTION

Cone-beam CT ?CBCT? is being increasingly used in modern

radiation therapy for patient setup, dose verification, and

adaptive replanning. However, the applications of CBCT are

still limited due to its inferior image quality as compared to

that of conventional CT. One major source of the poor image

quality is the high scatter signals in CBCT due to the large

illuminationvolumeand

organs.1Scatter causes severe shading and streak artifacts,

which greatly reduce the efficacy of image-guided radiation

therapy. For example, dose calculation from CBCT images is

a critical step in adaptive radiation therapy.2Although some

research has shown that high accuracy of dose reconstruction

can be achieved using CBCT images,3the applications of

these techniques are mainly limited to imaging of small vol-

umes, such as head and neck, where scatter signals are small.

In the case of imaging on a human torso, the accuracy of

dose reconstruction using CBCT images is not satisfactory

for clinical applications,4if no effective scatter correction

method is applied. The goal of this work is to develop an

effective scatter correction method for CBCT to facilitate the

use of CBCT in radiation therapy.

complicatedinhomogeneous

Many scatter correction methods have been proposed in

literature, and research in this field still remains very

active.5–11In general, these scatter correction methods can be

divided into two major types. The first type performs scatter

suppression during the acquisition of projection data based

on the difference between the incident angles of primary

photons and scatter photons. Typical examples include the

antiscatter grid method12and the air gap method.13These

methods achieve instant scatter suppression, although their

efficacy is usually limited. Siewerdsen et al., for example,

showed that an antiscatter grid was effective only in improv-

ing the contrast-to-noise ratio of low resolution CT images.12

An antiscatter grid attenuates primary photons as well, and

the imaging dose therefore needs to be increased to maintain

the image quality. Kyriakou and Kalender reported that this

dose increase is very significant if the scatter is high.10To

overcome these drawbacks, much effort has been devoted to

the scatter correction methods in the second category. With

different strengths and drawbacks, the methods in this cat-

egory correct for scatter using postprocessing techniques on

scatter contaminated projection images.6,7,11,14–16Although

improved scatter correction performances have been demon-

strated, a practical implementation usually involves a com-

bined consideration of different issues, such as correction

22582258Med. Phys. 36 „6…, June 20090094-2405/2009/36„6…/2258/11/$25.00© 2009 Am. Assoc. Phys. Med.

Page 2

efficacy, computation complexity, dose or scan time increase,

and hardware compatibility. A standard scatter correction

method for CBCT still remains elusive.

In current radiation therapy, one or two CBCT scans are

performed on the same patient every day, and the whole

treatment course typically lasts 4 to 6 weeks. Although the

existing scatter correction methods can be implemented for

CBCT in radiation therapy, they do not utilize the feature of

repetitive scans and requires scatter measurement/calculation

work for each CBCT scan. The complication of scatter re-

moval arises from the complicated dependence of the scatter

on the patient geometry, imaging parameters, and relative

position of the patient and the imaging system. In this work,

we propose a novel scatter correction method that is particu-

larly useful for CBCT in radiation therapy. The central idea

of our approach is to obtain a patient-specific scatter data-

base on the first day of the patient’s visit. In a subsequent

scan of the same patient on a different day, the prestored

scatter distributions are then used for scatter correction after

an appropriate transformation based on the patient’s on-

treatment geometry. During the patient setup in the first scan,

a partially blocked CBCT is used to measure the scatter dis-

tributions. An x-ray beam blocker with a strip pattern is in-

serted between the x-ray source and the patient such that

partial volume can still be accurately reconstructed and the

whole-field scatter distribution can be estimated from the

measured signals in the shadow regions using interpolation/

extrapolation. In the subsequent regular scans on the same

patient on different days, the patient transformation is first

determined using a rigid registration of the conventional

CBCT and the partial CBCT from the scatter measurement

scan. Based on the derived patient transformation, the mea-

sured scatter from the first scan is then modified accordingly

and used for scatter correction in the regular CBCT scans.

The proposed method is evaluated using physical experi-

ments on a clinical CBCT system.

II. METHOD

II.A. Scatter correction scheme

The general scatter correction scheme is shown in Fig. 1.

We first estimate scatter using a partially blocked CBCT in

the first CBCT scan during the treatment course of radiation

therapy. The estimated scatter distributions are stored and

used for scatter correction for the same patient in the subse-

quent scans on different days. The same imaging parameters

are used in these CBCT scans. However, the scatter distribu-

tions still change for different scans due to the small trans-

formations of the same patient. In order to estimate the scat-

ter distributions from the premeasured data, we reconstruct

the images using the partially blocked CBCT projections and

the regular CBCT projections. The partially blocked CBCT

and the regular CBCT images provide a precise rigid regis-

tration, as shown in our previous study.17Based on the rela-

tive geometric information, the premeasured scatter distribu-

tions are modified accordingly to generate scatter estimates

for the regular CBCT scan. These estimated scatter distribu-

tions are finally subtracted from the projection data for scat-

ter correction. Details of these procedures are discussed

below.

II.A.1. Partially blocked CBCT and scatter

measurement

The geometry of the partially blocked CBCT system is

shown in Fig. 2. The lead strips are aligned in the lateral

direction and block the incident x-ray photons. When a stan-

dard filtered-backprojection reconstruction is used for the

circular CBCT scan, the filtering on the projection data is

applied only in the lateral direction. Based on the classic CT

reconstruction theory, reconstruction of the partially blocked

CBCT scan is still complete for certain axial slices. Inside

the strip shadows on the detector, no primary signals are

detected and the measured signals provide scatter samples.

Assuming that the insertion of the lead strips does not greatly

perturb the shape of the scatter distributions in the cone-

beam ?CB? projection and scatter contains dominant low-

frequency signals,6,7,18we can estimate the scatter distribu-

tion of the whole field in a regular CB projection using the

measured scatter samples.

no i t c u r t s noc eR

no i t cu r t s no c eR

d i g iR

o i t a r t s i g e rn

CBCT Projection

Partial CBCT projection

e t ami t s er e t t a cS

e t ami t s e

r e t t a c s”

d

e r e t s i g

eR“

no i t c a r t buS

s no i t c e j o r pde t c e r r ocr e t t a cS

no i t cu r t s no c eR

TCde t c e r r oc

gami

r e t t a cS

e

r e t t a cS

o i t am i t s en

FIG. 1. Work flow of the scatter correction using prior scatter measurement

from partially blocked CBCT.

x-ray source

detector

patient

axis of rotation

beam-block strips

lead strip

FIG. 2. Geometry of the partially blocked CBCT system.

2259 Zhu et al.: Scatter correction for CBCT in radiation therapy2259

Medical Physics, Vol. 36, No. 6, June 2009

Page 3

To avoid the edge effect of the strips, only the measured

data inside the central one-third of the strip shadows are used

in the scatter measurement. The data inside the one strip

shadow are first averaged in the longitudinal direction to

reduce the noise in the measurement. A moving-average fil-

tering with a width of 9 detector pixels is then applied in the

lateral direction to further smooth the scatter distribution.

This smoothing filter is chosen empirically based on the

MonteCarlo

?MC?

simulation.

dimensional ?1D? profiles are the measured scatter at the cen-

ters of the strip shadows. A cubic spline interpolation/

extrapolation is then carried out in the longitudinal direction

to estimate the scatter distribution of the whole detector area.

Assuming that the scatter magnitude is proportional to the

illuminated volume,1to obtain a scatter estimate in a regular

CBCT projection, the scatter estimate in the partially blocked

CBCT projection is finally magnified by the ratio of the total

detector area to the illuminated detector area. For simplicity,

hereafter, we refer to the scatter estimate from the partially

blocked CBCT projections as the measured scatter.

The principle of our scatter estimation is similar to that in

conventional measurement-based methods.7,14,19However,

instead of using a two-dimensional ?2D? beam-block array

which in general can provide more accurate scatter measure-

ment for CB projections, we use a beam blocker with a 1D

strip pattern. This design is based on two reasons. First of all,

using projections of our proposed partially blocked CBCT

system, the reconstructed image is still complete in certain

slices in the axial direction. Therefore, an accurate registra-

tion is achievable using the partially blocked CBCT and the

regular CBCT. The derived geometric information is critical

to modify the premeasured scatter distribution for scatter cor-

rection of the regular CBCT. Secondly, the strip pattern

downsamples the scatter distribution longitudinally and the

longitudinal high-frequency scatter content cannot be esti-

mated. Therefore, the accuracy of the proposed scatter esti-

mation is heavily dependent on the assumption that scatter

has dominant low-frequency signals in the longitudinal di-

rection. As shown in our previous studies6,20and MC simu-

lations in Sec. III, the scatter in an x-ray projection of diag-

nostic imaging on an object with a quasicylindrical shape,

such as a human torso, contains high-frequency content only

in the lateral direction. Therefore, the scatter measurement

using the proposed strip beam-block pattern can still achieve

a high accuracy in clinical applications.

Theobtained one-

II.A.2. Image registration of a partial CBCT and a

regular CBCT

To derive the patient transformation used in the scatter

correction algorithm which will be described later, the regu-

lar CBCT data are first reconstructed without scatter correc-

tion. A rigid registration of the reconstructed volumes of the

partial CBCT and the regular CBCT is then carried out. The

Insight Toolkit ?ITK? is used in our implementation. To im-

prove the registration accuracy, the reconstructed images are

first thresholded and only the bone structures are used for

registration.21The cost function chosen for minimization is

the mean square pixelwise difference between the volumes.

The registration uses versors and a 3D translational vector to

describe the 3D rigid motion. The optimization method is a

gradient descent search algorithm. Furthermore, to accelerate

the registration, we generate a multiresolution image pyra-

mid. Low resolution versions of the datasets are first regis-

tered, and then higher resolution versions are subsequently

registered. The initial conditions are chosen by first placing

both datasets in the same coordinate system and aligning

their centers of masses. Typically, after approximately 100

steps, the step size decreases below a chosen threshold value

and the registration is completed.

II.A.3. Scatter correction based on the registration

of reconstructed volumes

Scatter distributions for the same patient change in differ-

ent CBCT scans due to different patient positions. Even if the

same imaging parameters are used and a rigid transformation

of the patient is assumed for different scans, an accurate

relationship between scatter distributions and the patient po-

sition is in general very complicated. Using a registration of

the partially blocked CBCT and the regular CBCT, we pro-

pose an approximate formula to calculate the scatter distri-

bution of a regular CB projection from the premeasured scat-

ter distributions.

CBCT projections are functions of three arguments: The

lateral and longitudinal detector coordinates u and v, and the

projection view angle ?. A rigid transformation on the pa-

tient can be described by six parameters: Translations in the

x, y, and z directions ?tx, ty, and tz? and rotations around the

x, y, and z axes ??x, ?y, and ?z?. In our definition of trans-

formation, the rotation is performed before the translation.

The coordinate systems are shown in Fig. 3?a?.

In a parallel-beam geometry, the scatter distribution is

shifted as the patient is translated. We assume that this prop-

erty of shift invariance is still a good approximation in a

divergent CB geometry. When the patient is translated with-

out rotation, we approximate the scatter distributions by

shifting the original scatter distributions as if in a parallel-

beam geometry. Equivalently, we assume that the scatter dis-

tribution shifts together with the projection of the patient

center on the detector. The distance of shifting is calculated

as the patient translation in the direction parallel to the de-

tector multiplied by a magnification factor determined by the

CB geometry.

Figure 3?b? shows the coordinate system when the patient

is shifted by tx, ty, and tzin the directions of the x, y, and z

axes, respectively. Correspondingly, the patient center moves

from O to O?, and O? is the projection of O? on the detector.

Now the goal is to find the shifts on the detector, tuand tv,

i.e., the position of O?.

Denote M as the magnification factor from O? to the de-

tector, SID as the source-to-imager distance ??SS???, and SAD

as the source-to-axis distance ??SO??. Based on the geometry,

M can be calculated as

2260 Zhu et al.: Scatter correction for CBCT in radiation therapy2260

Medical Physics, Vol. 36, No. 6, June 2009

Page 4

M =?SS??

?SB?=

?SS??

?SO? + ?OB?=

SID

SAD+ txcos ? + tysin ?,

?1?

and tuand tvare calculated as

tu= M?O?A? = M?− txsin ? + tycos ??,

?2?

tv= M?AB? = Mtz.

?3?

Denote Smas the measured scatter obtained from the par-

tially blocked CBCT projections and Seas the scatter distri-

bution in the regular CBCT projections that we need to esti-

mate. Based on the approximation discussed earlier, we

calculate Seas

Se?u,v,?? = Sm?u + tu,v + tv,??.

?4?

Note, however, that the above approximation assumes no

patient rotation. When the patient rotates during the transfor-

mation, however, Eq. ?4? becomes much less accurate. For-

tunately, in practice of radiation therapy, a patient rotation is

typically very small ?less than 2°? after the standard patient

setup.22Therefore, we can safely assume zero patient rota-

tion about the x and y axes, i.e., ?x?0 and ?y?0. Rotation

about the z axis, ?z, can be easily included in the scatter

estimation formula by shifting the rotation angle ? since the

axial rotation is equivalent to a change in the starting angle

of the CBCT scan. The final estimation formula of Seis

expressed as

Se?u,v,?? = Sm?u + tu,v + tv,? + ?z?,

where tuand tvare calculated using Eqs. ?1?–?3?.

Equation ?5? is the main scatter estimation formula used

in this article. The formula shows that the scatter can be

estimated by shifting the premeasured scatter distributions in

all three directions. A cubic spline extrapolation is used when

the index of estimated scatter is outside the space of the

premeasured scatter. Several approximations are made in the

algorithm derivation. Detailed discussion on the assumptions

of the imaging geometry and patient transformation will be

provided in Sec. IV.

The estimated scatter is subtracted from the measured

projection to generate scatter-corrected data. Note that, as

generally true in scatter correction using postprocessing tech-

niques, the scatter noise is left in the processed image.23A

penalized weighted least-squares algorithm is implemented

to suppress the image noise.24,25The data are then processed

using a standard Feldkamp–David–Kress cone-beam CT

reconstruction.26

?5?

II.B. Evaluation

The measurement of scatter distribution using the pro-

posed partially blocked CBCT is based on the assumption

that for imaging on a human torso, the scatter distribution

contains dominant low-frequency signals in the longitudinal

direction. We validated this assumption using MC simula-

tions ?GEANT4? on the Zubal phantom.27The implementation

details of the MC simulation can be found in Ref. 6.

A MC simulation of a complete CT scan is very time

consuming, and the proposed method was further evaluated

using physical experiments. The CBCT imaging system used

in this work was a Varian Acuity CT simulator ?Varian Medi-

cal Systems, Palo Alto, CA?. A standard imaging protocol as

in clinic was applied. The x-ray tube was operated at

125 kVp voltage and 80 mA with the pulse width at each

projection angle of 25 ms. A bow-tie filter was placed on in

order to maintain a more uniform photon statistics across the

field of view ?FOV?. Data of a 360° scan consisted of about

680 projections with an angle interval of about 0.5°. The

dimension ofeach acquired

397.3 mm?298.0 mm, containing 1024?768 pixels. The

SAD was 1000 mm and the SID was 1500 mm. To increase

the FOV, a half-fan mode was used, with the flat-panel de-

tector shifted by approximately 160 mm.

In the partially blocked CBCT, the sheet of lead strips was

mounted on the outside surface of the collimator with a dis-

tance of approximately 400 mm to the x-ray focal spot. The

strips had a thickness of approximately 2 mm with an x-ray

attenuation of over 99%. The strip spacing determines the

sampling rate of the scatter distribution. Based on MC simu-

projectionimage was

u

v

x

y

z

S

O

β

p(u,v)

detector

focal spot

(a)

S??

u

v

S

O?

y

p(u,v)

detector

focal spot

(b)

(tx,ty,tz)

O??(tu,tv)

S??

A

B

C

D

x

z

O

β

FIG. 3. The cone-beam projection geometry and coordinate systems. ?a?

coordinate systerm before transformation; ?b? coordinate system after the

object translates by tx,ty,tzin the directions of the x, y, and z axes,

respectively.

2261 Zhu et al.: Scatter correction for CBCT in radiation therapy 2261

Medical Physics, Vol. 36, No. 6, June 2009

Page 5

lations, in our design, the strip had a width of approximately

6 mm and a gap of approximately 3 mm in between. The

shadows of the strips on the detector have a width of ap-

proximately 24 mm and a gap of approximately 12 mm, re-

sulting in a scatter sampling period of ?36 mm on the de-

tector. As shown in the results of experiments, this sampling

period is chosen based on MC simulations and achieves a

satisfactory accuracy of scatter estimation.

Two phantoms were used in the experiments. The first

was the Catphan©600 phantom with a diameter of 200 mm.

To increase the illumination volume such that the scatter

magnitude is comparable to that in a scan on a human torso,

we placed an oval body annulus in the periphery to expand

the phantom to an elliptical cylinder with a major axis of

380 mm and a minor axis of 300 mm. An anthropomorphic

chest phantom was used in the second study. In both experi-

ments, we first measured the scatter using a partially blocked

CBCT scan. The phantom was then transformed to simulate

the patient transformation in scans on different days, and the

proposed scatter correction was applied on a second regular

CBCT scan.

Comparisons of the reconstructed images and 1D profiles

of the regular CBCT scans are provided to illustrate the per-

formance of the proposed method. In the experiments of the

Catphan©600 phantom, to provide a benchmark image, the

phantom was reconstructed using a narrow collimator, where

the scatter was inherently suppressed. In this setup, the field

of illumination on the detector has a width of ?1 cm in the

longitudinal direction and the geometry is equivalent to a

fan-beam projection. The body annulus was also removed to

further reduce the scatter. In the quantitative analysis, recon-

structed values are converted to Hounsfield unit ?HU? in se-

lected regions of interest ?ROI? and compared to those in the

benchmark image. The error is calculated as the square root

of the mean square error ?RMSE?, defined as

RMSE=?mean???i− ? ¯i?2?,

?6?

where i is the index of the ROI, ?iis the mean reconstructed

value in HU inside the ROI, and ? ¯iis the corresponding

value measured in the benchmark image. In the experiment

of the anthropomorphic phantom, the CBCT images before

and after scatter correction are also compared to that using a

narrow collimator. The error is quantified as the relative re-

construction error ?RRE? in the ROI, defined as

RRE= 100%?mean??v?x,y? − v ¯?x,y?

v ¯?x,y??

2?,

?x,y? ? ROI

?7?

where v is the reconstructed value in mm−1and v ¯ is the

corresponding value using a narrow collimator. ?x,y? are the

coordinates of the reconstructed image. Since the z direction

coverage is very small using a narrow collimator, only 2D

slices are compared. The ROI is chosen as the nonair re-

gions, which are determined by thresholding.

III. RESULTS

III.A. Monte Carlo simulation

Figure 4 shows the Zubal phantom, one simulated projec-

tion of the chest region, and its corresponding scatter distri-

bution. It is seen that the scatter distribution contains very

low-frequency signals in the longitudinal direction, as also

????? ???????

??????????

???????

FIG. 4. MC simulation on the Zubal phantom.

100 200 300 400500

Pixel

600 700800900 1000

0

2

4

6

8

10

12

14

16

18

20

Magnitude

(a)

50 100150200 250

Pixel

300 350400450 500

0

2

4

6

8

10

12

14

16

18

20

Magnitude

(b)

FIG. 5. 1D profiles of the scatter distribution shown in Fig. 4. Note that the

same scale is used in both plots. ?a? Central horizontal profile; ?b? Central

vertical profile.

2262Zhu et al.: Scatter correction for CBCT in radiation therapy 2262

Medical Physics, Vol. 36, No. 6, June 2009

Page 6

shown in Fig. 5. This reveals that the proposed partially

blocked CBCT is able to provide an accurate scatter mea-

surement.

To provide a design guidance of the lead strips used in the

partially blocked CBCT, we carry out scatter estimation on

the simulated data using the method presented in Sec. II A 1

with different longitudinal sampling periods. The result is

shown in Fig. 6. The estimation error in percentage is calcu-

lated as the error relative to the true scatter signals in a simi-

lar way as shown in Eq. ?6?. On the chest region of the Zubal

phantom, a longitudinal sampling period on the detector not

larger than 40 mm guarantees a scatter estimation accuracy

of over 99%. Note that the penumbra edge effects due to the

finite size of the focal spot are not included in the MC simu-

lation. In reality, to avoid scatter estimation errors from these

effects, the sampling period cannot be very small. Based on

this consideration, we chose ?36 mm as the longitudinal

sampling period of the lead strip pattern.

III.B. Experiments on the Catphan©600 phantom

Figure 7 shows experimental results on the Catphan©600

phantom. In the regular CBCT scan after the partially

blocked CBCT data acquisition, the phantom was translated

laterally by 10 mm and longitudinally by 10 mm, i.e., ty

=10 mm, tz=10 mm. Reconstructions of the regular CBCT

scan are shown. As seen in Fig. 7?a?, shading/cupping arti-

facts are severe in the reconstructed images if no scatter cor-

rection is applied. Note that the scatter artifacts have a non-

typical and complicated pattern due to the use of a bow-tie

filter and an offset flat-panel detector.28These artifacts are

suppressed when a simple software correction scheme is

used ?Fig. 7?b??. In this scheme, we assume that the scatter is

constant across the whole projection field, and its magnitude

is estimated based on the volume size of x-ray illumination

as described in Ref. 1. Nonetheless, new distortions are ob-

vious around the center of the image. A superior image qual-

ity is found in Fig. 7?c?, where the scatter is corrected for

using the proposed method. The scatter artifacts are greatly

suppressed without inducing new artifacts. To illustrate the

importance of estimating scatter using Eq. ?5? based on the

relative object geometry, we show in Fig. 7?d? the recon-

structed image with the scatter corrected directly using the

measured scatter, i.e., assuming that Se=Sm. Distortion ap-

pears in the images, which indicates the necessity of scatter

estimation using Eq. ?5?.

a)

b)c) d)

FIG. 7. Axial views of the reconstructed Catphan©600 phantom. Display window: ?−500 500? HU. In the regular scan after partial CBCT, the object is

translated ?ty=10 mm, tz=10 mm?: ?a? No scatter correction; ?b? using constant scatter correction; ?c? scatter corrected using the proposed method; and ?d?

scatter corrected using the measured scatter from the partial CBCT, but without using the “registration” algorithm as defined in Eq. ?5?. The white arrow

indicates the image distortion.

FIG. 8. Reconstruction of the Catphan©600 phantom using a narrow colli-

mator ?a fan-beam geometry?.

0 10 2030 4050 607080

0

0.5

1

1.5

2

2.5

3

3.5

4

Longitudinal sampling period on the detector (mm)

RMSE (%)

FIG. 6. Relationship between the scatter estimation error and the sampling

period based on the MC simulation.

2263Zhu et al.: Scatter correction for CBCT in radiation therapy2263

Medical Physics, Vol. 36, No. 6, June 2009

Page 7

For a better comparison, we obtain a benchmark image

?Fig. 8? of the Catphan©600 phantom without the body an-

nulus and using a fan-beam geometry. The fan-beam geom-

etry was implemented using a narrow collimator, as de-

scribed in Sec. II B. The benchmark image is registered to

the images shown in Fig. 7. Figure 9 shows the comparison

of 1D profiles passing through one contrast object. The

benchmark image does not include the body annulus, and

therefore the reconstruction data of the body annulus are ex-

cluded in the comparison. The reconstruction error due to

scatter, such as signal intensity drop and contrast loss, is

obvious in Fig. 9. This error is greatly suppressed using the

proposed method, and the scatter correction result matches

the benchmark image well.

To test the stability of the proposed method, Fig. 10

shows the images with and without scatter correction when

the object has different transformations in four regular CBCT

scans. In the first scan, the phantom has no transformation; in

the second and the third scans, the phantom is shifted later-

ally by 10 and 20 mm ?ty=10 mm and ty=20 mm?; in the

fourth scan, the phantom is shifted laterally by 5 mm and

also rotated about the x axis by 3° ?ty=5 mm, ?x=3°?. Seven

contrast rods as shown in Fig. 8 are selected as the ROIs.

Table I summarizes the reconstruction values in HU in the

ROIs and the errors relative to the values obtained in a fan-

beam geometry. Both the image comparison and quantitative

analysis indicate that the proposed method is very effective

on scatter correction even if the object has a small rotation

which violates the assumption in the algorithm derivation.

The reconstruction error is reduced from about 350 HU to

below 50 HU. Note that the residual reconstruction error af-

ter scatter correction increases as the object transformation

gets larger. However, we want to emphasize that the patient

setup error in radiation therapy treatment is typically less

than 10 mm in translation and less than 2° in rotation.22Our

method is expected to achieve excellent scatter correction in

practice.

III.C. Experiments on the anthropomorphic phantom

One partially blocked CB projection of the anthropomor-

phic chest phantom and its corresponding measured scatter

distribution is shown in Fig. 11. In the regular CBCT scan,

the phantom is slightly transformed. Using a rigid registra-

tion, the calculated transformation parameters are tx=

−4.0 mm, ty=8.4 mm, tz=−2.2 mm, and ?x=2.01°, ?y

=1.99°, ?z=0.55°. Figure 12 shows one regular CB projec-

tion and its scatter estimate using the proposed method.

Figure 13 shows the axial views of the reconstructed vol-

umes without and with scatter correction and using a fan-

180 200220 240260

pixel

280300 320340360

−1000

−800

−600

−400

−200

0

200

400

600

800

reconstructed value (HU)

without scatter correction

using constant scatter correction

using the proposed method

using a fan−beam geometry

FIG. 9. Comparison of 1D profiles in Figs. 7 and 8 passing through one

contrast rod. The data on the body annulus are excluded.

a)b) c) d)

FIG. 10. Axial views of the reconstructed Catphan©600 phantom with different transformations in the second regular CBCT scan. Display window:

?−500 500? HU. Upper row: Without scatter correction; bottom row: Using the proposed method: ?a? No transformation; ?b? ty=10 mm; ?c? ty=20 mm; and

?d? ty=5 mm, ?x=3°. The transformation parameters ?tx,y,zand ?x,y,z? are zeros unless otherwise specified.

2264Zhu et al.: Scatter correction for CBCT in radiation therapy2264

Medical Physics, Vol. 36, No. 6, June 2009

Page 8

beam geometry. The image distortion and shading artifacts

due to scatter are greatly suppressed by using the proposed

method. The quality of the scatter corrected image is close to

that using a fan-beam geometry, which is also illustrated in

the 1D profile comparison as shown in Fig. 14. The sagittal

and conoral views without and with scatter correction are

shown in Fig. 15. It is obvious that the proposed algorithm

greatly suppresses the shading artifacts mostly surrounding

the bones. The proposed method reduces the RRE value as

defined in Eq. ?7? from 15.7% to 5.4%. To investigate the

performance of the proposed scatter estimation from the scat-

ter measurement ?Eq. ?5??, we include a fourth image ?Fig.

13?b?? in the comparisons of Figs. 13 and 14. After the phan-

tom is transformed, another scatter measurement is carried

out using the partially blocked CBCT. The image is then

generated using scatter correction directly based on the scat-

ter measurement. It is seen that the measurement-based scat-

ter correction has a similar performance as compared to the

proposed method. Therefore the proposed approximation for-

mula ?Eq. ?5?? provides an accurate scatter estimation for this

phantom scan.

IV. DISCUSSION AND CONCLUSIONS

An effective scatter correction method for CBCT in radia-

tion therapy is proposed in this study. The development of

this method is inspired by the fact that the same patient is

scanned repetitively during the radiation treatment course.

Assuming that the same imaging parameters are used, the

scatter signals are closely correlated in these scans. There-

TABLE I. Comparison of reconstruction values ?in HU? inside the contrast rods of the Catphan©600 phantom.

The minimum and maximum of the errors are also shown in parentheses.

ROI1234567 RMSE ?min?max?

Fan-beam 367.5958.6 −954.7 −159.8

No scatter correction

−482.1 −160.7 −142.3 −149.5 −536.7 347.6 ?−595.8?472.6?

−502.0 −166.3 −143.9 −141.8 −526.5 351.8 ?−615.2?452.7?

−473.0 −143.9 −137.8 −166.3 −555.6 347.4 ?−605.0?481.7?

−480.6 −146.9 −134.2 −145.4 −533.7 353.0 ?−617.8?474.1?

−504.6 −156.1 −152.0 −152.0 −518.9 350.3 ?−594.8?450.0?

−66.5 −11.5 −950.9

No transformation

ty=10 mm

ty=20 mm

ty=10 mm, tz=10 mm 104.6

ty=5 mm, ?x=3°

100.5

84.7

119.9

362.8

343.4

353.6

340.8

363.869.4

Using the proposed method

−937.8 −156.6

−957.1 −160.7

No transformation

ty=10 mm

ty=20 mm

ty=10 mm, tz=10 mm 312.8

ty=5 mm, ?x=3°

359.7

323.0

383.2 1035.7 −1016.8 −143.4

924.5

351.5971.4

978.6

978.1

−72.4

−62.2

−72.4

−46.9

−73.0

−28.6 −970.9

1.0 −957.7

−58.2 −958.7

−23.0 −897.0

−15.3 −985.2

14.6 ?−20.0?20.0?

19.2 ?−44.5?19.5?

42.4 ?−62.1?77.1?

38.6 ?−54.7?54.0?

17.9 ?−34.3?14.9?

−907.7 −134.7

−974.0 −144.9

(a) Partially blocked CB projection.(b) Measured scatter distribution.

FIG. 11. Projection image of partially blocked CBCT

and the corresponding measured scatter distribution.

(a) Regular CB projection.(b) Estimated scatter distribution.

FIG. 12. CB projection image and its scatter estimate

using the proposed method.

2265Zhu et al.: Scatter correction for CBCT in radiation therapy2265

Medical Physics, Vol. 36, No. 6, June 2009

Page 9

fore, we can measure the scatter distributions in the first scan

and perform scatter correction in the subsequent scans on the

same patient on different days. A partially blocked CBCT is

used to measure the scatter distributions, as well as to obtain

the geometric information of the patient. An approximate

formula is also proposed to estimate the scatter distributions

in the subsequent regular scans based on the geometric in-

formation. The method is evaluated using experiments and

shows significant suppression of scatter artifacts. On the Cat-

phan©600 phantom, the reconstruction errors in the selected

ROIs are reduced from about 350 to below 50 HU; on the

anthropomorphic phantom, the reconstruction error is re-

duced from 15.7% to 5.4%. Note that our method is different

from the existing measurement-based scatter correction

methods,7where an additional scan with an insertion of a

beam blocker is used only for the purpose of scatter mea-

surement and therefore the patient dose is increased. In the

proposed method, the partially blocked CBCT scan not only

provides an accurate scatter measurement but also can be

used for precise patient setup with a much decreased patient

dose.17In the current radiation therapy where CBCT is

mainly used for patient setup, the scatter measure from a

partially blocked CBCT scan is “free” information. In our

algorithm, several additional steps are added into the conven-

tional data processing chain. The increased computation

complexity mainly resides on the extra 3D reconstruction on

the regular scan. Nonetheless, with new developments of

computer technology, CT reconstruction is dramatically

accelerated.29,30The proposed method can still be considered

as a viable and practical solution to the scatter problem in

CBCT.

The underlying philosophy of our method is to create a

patient-specific scatter database and correct for scatter for

different scans based on patient geometric information. In

our implementation, a partially blocked CBCT scan is used

to measure the scatter. In applications where partial blocking

of the detector is not desired, such as in fiducial tracking

using CB projections, other methods can also be used here to

obtain the scatter data. For instance, since the planning CT

data from the multidetector CT scanner are readily available,

we can generate the scatter data using an analytical model18

or a MC simulation.11

Due to the complex nature of scattering process, approxi-

mations are made to simplify the derivation of the scatter

modification formula based on the measured scatter distribu-

tions and the patient geometric information. These approxi-

mations work well in the experiments. We also assume that a

rigid transformation applies on the patient. In practice, the

patient has deformations in different scans, and the deforma-

tion not only changes the scatter distributions but also affects

the correlation of the patient geometries. However, since the

point spread function of the scatter is typically smooth,18

scatter distributions are very insensitive to small patient de-

formations. When the patient deformation is large, a partially

blocked CBCT scan can be implemented right before the

regular scan to provide a more accurate scatter measurement

at the price of extra patient dose. Future investigations on the

accuracy of the proposed algorithm under the circumstance

of patient deformation is of high interest using clinical pa-

tient studies.

The proposed method is evaluated using experiments with

different transformations. The scatter estimation is expected

to be less accurate as the patient transformation increases.

For example, as the translation increases, due to the half-fan

geometry in clinical Varian CBCT systems, the illumination

a) b) c)d)

FIG. 13. Axial views of the reconstructed anthropomorphic phantom. Display window: ?−800 450? HU. In the regular scan after partial CBCT, the phantom

is transformed by parameters of tx=−4.0 mm, ty=8.4 mm, tz=−2.2 mm, and ?x=2.01°, ?y=1.99°, ?z=0.55°: ?a? No scatter correction; ?b? measurement-based

scatter correction using a partially blocked CBCT as a prescan; ?c? scatter corrected using the proposed method; and ?d? using a narrow collimator ?a fan-beam

equivalent geometry?. The line in ?a? indicates the location where the 1D profiles shown in Fig. 14 are taken.

200250 300350400

−1000

−500

0

500

pixel

reconstructed value (HU)

without scatter correction

using scatter measurement for correction

using the proposed method

using a fan−beam geometry

FIG. 14. Comparison of 1D vertical profiles in Fig. 13.

2266Zhu et al.: Scatter correction for CBCT in radiation therapy2266

Medical Physics, Vol. 36, No. 6, June 2009

Page 10

volume size is more different in different scans, causing dif-

ferent scatter magnitudes. The use of a bow-tie filter makes

the difference even larger. The overlapping projection area

becomes smaller as well, resulting in scatter estimation error

due to excessive signal extrapolation. The proposed algo-

rithm also assumes that the patient has only in-plane rotation,

i.e., no rotations about x and y axes. Further research will be

conducted to expand the proposed method to more accu-

rately estimate the scatter for arbitrary rigid transformations

of the object. It is worth mentioning that in radiation therapy,

the patient transformation is typically less than 10 mm in

translation and less than 2° in rotation after the patient

setup,22and the setup error can be further reduced using

in-line cone-beam CT.31The object transformations used in

our experiments are within or beyond the range of patient

setup errors, and excellent scatter correction results are

shown. Therefore, we expect our algorithm to work well in

clinical applications.

The indication of the presented work is multifold. First,

the proposed method greatly improves the soft-tissue con-

trast of CBCT, which enables clinicians to make better clini-

cal decisions. Second, the increased HU accuracy can greatly

improve the accuracy of dose reconstruction using CBCT

images, which makes treatment planning using CBCT im-

ages a viable option. As such, the improved image quality

using the proposed scatter correction method should be very

attractive in clinical applications.

ACKNOWLEDGMENTS

This project was supported in part by grants from Na-

tional Cancer Institute ?Nos. 1R01 CA98523 and CA104205?

and Department of Defense ?W81XWH-08-1-0127?. The au-

thors would like to thank Triple Ring Technology for provid-

ing the anthropomorphic phantom. They also acknowledge

Jared Starman for his help with the article revision.

a?Electronic mail: leizhu@stanford.edu

b?Current address: Beijing Key Laboratory of Medical Physics and Engi-

neering, Peking University, Beijing 100871, China.

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