introduction to digital radiography - welcome|radiation imaging...

INTRODUCTION TO DIGITAL RADIOGRAPHY

Ho Kyung Kim, [email protected]

School of Mechanical EngineeringPusan National University

Radiation Imaging Lab {bml.pnu.edu}School of Mechanical Engineering, Pusan National UniversityHo Kyung Kim {[email protected]}

Outline

• Brief overview of DR-detector configurations and principles

• Comments on the design considerations

• Imaging performances of DR detectors

• Applications of FPDs

• Prospects in the near future

2


Take-home messages

• Two fundamental radiation-detection principles: Recombination & ionization

• Two different schemes of x-ray detection in digital radiography detectors: Direct vs. indirect-conversion schemes

• Role of "gain-offset correction" in digital radiography

• Concept of Fourier-based image-quality metrics: MTF, NPS, & DQE

• Energy-discriminating, depth-discriminating radiographs; how can we get them?

• Differences between energy-integrating and photon-counting imaging

3


Roentgen vs. Me

4

WC Roentgen, Dec. 22, 1895 HK Kim, Sept. 19, 2009

113 years gap


Why’ve been so slow in progress?

• The size does matter.– Limited size of available imagers (e.g. CCD,

CMOS photodiode arrays)– Availability of big size wafer– Marginable production yield in the wafer-

based process

5

17”

14” 17”

17”

• Radiation hardness of silicon or other materials for electronic imagers

• Computed radiography (CR) based on photostimulable phosphors, introduced in the early 1980s by the Fuji Photo Film Co., has been used until now (and still after).

CCD, LBNL

Taken picture from MJ Flynn’s Lecture Slides


Tricks

• Utilization of the conventional, small-size photo-imagers (e.g. CCD, CMOS) but,

– With various mechanical motions;• May provide a better image quality

due to the scatter rejections• But, can we finish scanning within a

single heart beat?

6

MJ Yaffe and JA Rowlands, PMB (1997)

– By coupled with optics;

• But, very special caution should be devoted when designing optics systems

• e.g. = 1.5% ( = 0.8, M = 0.5, & F = 1.2)

22

222

2

44)1(4M

FM

MFMM

Radiation Imaging Lab {bml.pnu.edu}School of Mechanical Engineering, Pusan National UniversityHo Kyung Kim {[email protected]} 7

Scanning radiography: panoramic radiography


Imaging Dynamic Co., Ltd., Canada

Lens-coupled DR system

CCD

X-ray

LightLens

Mirror


Poor light collection efficiency may results in a small number of electrons being produced for each absorbed x-ray photon, hence showing excess noise in images (secondary quantum sink)

Taken picture from MJ Flynn’s Lecture Slides


– By butting small-size imagers (mosaic method);

• But, should the butting-gap be as small as a pixel pitch

• Needed additional image processing techniques for interpolation between gaps and different signal responses between the detector modules

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– By stitching small-size imaging chips (or reticles) in wafer-process level.

• Ideally, there are no physical gaps between reticles

• But, also needed an additional image processing technique for different characteristics between reticles due to the nonuniform fabrication process over large area

Image courtesy of Dr. T. Achterkirchen, Rad-icon Imag. Corp. Image courtesy of Vatech & E-Woo

A pixel

< 50 m


Breakthrough

• Large-area flat-panel detectors (FPDs)– Motivated by large-area AMLCDs and initialized in the mid-1980s– Realization of 2D pixel arrays (TFT alone or a combination of TFT plus photodiode in a pixel) on

large-area glass substrate based on amorphous silicon process• Lower fabrication cost compared to the crystalline counterpart• Better radiation hardness• But, worse electrical properties & a high density of charge traps, which may result in image

lag & ghosting

11

Image Courtesy ofSamsung Electronics Co. & Vatech, Co., Ltd.

Scintillator to convertx-ray into light


Taken pictures from Dr. J Yorkston’s Slides

Image Courtesy of Anrad


Amorphous materials

• Availability in large area• Lower fabrication cost compared to crystalline devices • Better radiation hardness than crystalline devices• Worse electrical properties than crystalline devices• Charge trapping thru dangling bonds• Hydrogenated amorphous silicon, a-Si:H

13

SiHydrogenated

Uncoupled

Void


Recombination

14

Activator site

Valence band

Forbidden gap

Conduction band

EnergyEnergy


Ionization

• Radiation signal (or energy) Q I V digital signal

15

EnergyActivator site

Valence band

Forbidden gap

Conduction band


Detection principles

• Indirect-conversion FPDs– Converting x-ray into light, and then

electrical signals– Information sharing over several pixels

16

HK Kim, IA Cunningham, Z Yin, G Cho, IJPEM (2008)

Scintillator

Passivation

ITOp+

ViaIntrinsic

n+

Data lineBias line

GateSourceDrain

|E|

V – V

Glass substrate

Photoconductor

Top electrode

|E|

V – V

Pixel electrode

Storage capacitor

Glass substrate

• Direct-conversion FPDs– Converting x-ray into electrical signals

directly– No information sharing


Operation principles

17



Comparisons

Indirect-conversion FPDs Direct-conversion FPDs

X-ray converterScintillators

e.g. CsI:Tl, Gd2O2S:TbPhotoconductive semiconductorse.g. a-Se, HgI2, PbI2, PbO, CdZnTe

Readout pixel array TFT + photodiode TFT + pixel electrode (storage cap.)

Bias voltage -5 ~ -10 V higher (e.g. 10 V/m @ a-Se)

Fab. complication 12 ~ 14 masks 5 ~ 7 masks

Quantum efficiency higher lower (a-Se)

Image blurring Additional light scattering Within intrinsic x-ray interactions

Image sampling Lower aliasing Higher aliasing (white spectrum)

Amelioration

Higher intrinsic conversion eff.Less light scattering

Better optical couplingLess charge trapping

High Z materialsLower W-value

Lower dark currentLarger F

18



FPDs at home

19

매일경제, 2007.12.13.

연합뉴스, 2007.11.22.


Some practical considerations in the design of FPDs

• Pixel fill factor– Fractional area sensitive to signal in a pixel– Related directly to the detector signal and

noise aliasing– Mitigated with various approaches

• 3D configuration of pixel elements• Back to the silicon process???

• With elaborated, sophisticated pixel deigns, such as 3D configuration with poly-crystalline or crystalline silicon process, new imaging detector or technology would be expected.

– Active pixel sensor– Energy-specific imaging

20

Room for more elements


• Readout speed– Charge transfer time

• pix = 10 2.4 M 1 pF = 24 s– ADC time

• 1536 data lines = 128 / (5 MHz 0.5) = 51.2 s– Frame time = 1280 75 s = 96 ms (10 Hz)

21

From Dr. RA Street’s Text

panel

panelgate

gate

pdongateread

L

LCRdNCR

dCdRN

CRN

0000

200

1010

10

10

in msec

(in cm)

• A rule of thumb;


• Electronic noise

22

Noise sources Formalism

Estimated Noise (e–)in an FPD with a pixel

pitch of 100 m(40 x 40 cm2, 100 ms)

TFT thermal noise

490

TFT transient noise

PD shot + 1/f TFToff

PD shot + 1/f TFTon

TFT shot + 1/f TFToff

Data line thermal noise 2310

Preamplifier noise 560

ADC noise 120

Total noise 2430

pdkTCq

21

n

Ltrans f

fQq

11

n

LoffTFTleakpd f

fIq

11

n

LonTFTleakpd f

fIq

11

n

LoffTFTleakTFT f

fIq

11

01 fkTRCq datadata

01

316)(1 f

gkTCC

q mampdata

1221

bitssignalQ

q

LE Antonuk’s Group, Med. Phys. (2000)


• Imperfection in signal responses over the detector area due to;

– Variations in areal x-ray exposure;– Variations in sensitivity of x-ray converters;– Variations in sensitivity of readout pixel

arrays;– Variations of in gain & offset of peripheral

circuits;– Variations in signal transfer by

capacitive/resistive coupling thru metal lines;

– etc.

• For the reliable use of FPDs, the methods for the flood-fielding correction and abnormal pixel/line interpolation should be prepared.

23


Commercial products

GE Trixell Canon Hologic SwissRay DelftDetector name

Revolution Pixium 4600 CXDI 40G DirectRay dOd ThoraScan

Converter CsI:Tl CsI:Tl Gd2O2S:Tb a-Se CsI:Tl CsI:Tl

Thickness (m)

Undisclosed ~550 ~200 ~500 600 ~500

Readoutpixel array

a-Si:H PD/TFT

a-Si:H PD/TFT

a-Si:HMIS/TFT

a-Se TFTmirror + lens

+ 4 CCDsCCD (slot scanning)

Imaging area (cm)

41 x 41 43 x 43 43 x 43 35.6 x 42.7 35 x 43 44 x 44

Pixel format 2022 x 2022 3001 x 3001 2688 x 2688 2560 x 3072 2048 x 2560 2720 x 2720

Pitch (m) 200 143 160 139 169 162

Number of detectors

1 4 (2 x 2) 1 1 4 (2 x 2) 8 (8 x 1)

Geometric fill factor (%)

82 68 52 87 100 87

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Report 05078, Center for Evidence-based Purchasing (2005)


• Decision makers– Human observers– Quasi-ideal observers– Ideal observers (from Bayesian decision theory)

• Requires measurements of the signal (lesion), CTF, NPS

Which imaging system is the best for accurate diagnosis?

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Adapted from ICRU 1996

Distribution of actuallyabnormal cases

Decision axis

Distribution of actuallynormal cases

Decision threshold

True positive fraction

False positive fraction


Relationship between diagnostic performanceand physical image quality

• Image quality parameters– Large-scale system-transfer function– Spatial-resolution properties– Noise properties

26

Adapted from ICRU 1986

Dia

gno

stic

acc

urac

y

Physical image quality

• In Fourier domain (why do we need?)

– Modulation-transfer function (MTF)– Noise-power spectrum (NPS)


Signal (or contrast) correlation in space

• We cannot avoid the following intrinsic signal spreading factors;– Oblique incident of x rays– Energy-dependent range of the generated electrons– K-fluorescence reabsorption

27

converterconverter

x ray

cluster of optical quanta

• Modulation-transfer function (MTF) is typically used to describe signal spreading; )(lsf)(MTF xu F

Taken Sketches from IA Cunningham's Lecture Slides (SPIE 2008)


Noise correlation in space

• These two images have the same pixel variance, but different correlation structure.• Simple image pixel variance ignores second-moment statistics (correlation btwn pixels).• Noise-power spectrum is more appropriate;

29

Taken images from RF Wagner, AAPM (2004)

)(K)(NPS xu F


Image quality vs. patient dose

31

Picture used by Rose; taken from AE Burgess, JOSA (1999)

3 103 1.2 104

~105 ~8 105

2.8 1073.6 106

Image qualityPatient dose


Detective quantum efficiency (DQE)

• Fraction of incident quanta contributing to the image quality• Independent of dose (for quantum-noise limited case)• A measure of how well a detector is able to extract information from a beam of radiation

32

)(NPS)(MTF

)(SNR)(SNR)(DQE

22

2

2

kk

kkk

Gqin

out

Freq.

NPS

Freq.

1

MTF

ideal

sharpblurryuncorrelated

correlated


1 or 100%D

QE

Spatial frequency (mm-1)

( Deceasing detail size)

(H

ow w

ell a

det

ecto

r is a

ble

to e

xtra

ct

info

rmat

ion

from

a b

eam

of ra

diat

ion)

Converter efficiency;Swank noise; additive noise;fill factor; direct x-ray absorption …

Secondary quantum sinks;noise aliasing; reasorption noise …


Detector or system?

• Samei et al. have recently introduced the “effective” DQE to extend the concept of DQE for characterizing the performance of DR imaging systems;

35

E Samei et al., Radiology (2008)

qETFMSFM

NB

)(NNPS

)1()(MTF)(eDQE22

kkk

• The results imply that there is a large margin for improving the image quality of detectors while reducing patient dose.


• Secondary quantum loss– There are several layers between the bottom of

the overlying scintillator and the top of photodiode array for passivation and protection.

– These layers would not be perfectly transparent to the optical secondary quanta, which may result in serious secondary quantum sinks and would degrade the Swank noise factor.

Theoretical DQE

36

Cascaded systems analysisStage Physical process0 Incident quanta1 Interaction of x-ray quanta2 Conversion to secondary quanta3 Spread of secondary quanta4 Coupling of secondary quanta5 Integration by pixel aperture6 Sampling of pixel matrix7 Readout with additive noise

0 1 62B

2C

2A

3 4 5 7

A B C

Modified from J Siewerdsen’s Slides


• Consider two FPDs both based on CsI:Tl x-ray converters (indirect-conversion detectors)

37

Private communications with Dr. IA Cunningham


S. Yun et al., NIMA in press (2011)

2220

2

20

2

22

1111

)(sinc)()(DQE

ggg aqqI

aT

readgen

ρρρ

2220

2

20

2

2

1111

)(sinc)(DQE

ggg aqqI

a

readgen

ρρ


Optimization

39

NutaskDQE duuuWdindexityDetectabil '

02 )'(DQE)'(

Spatial frequency (mm-1)or “Object details”

Func

tion

Imaging taskObject information in terms of frequency

W12(u)

W22(u)

Detector performanceSNR efficiency as function of frequency

DQE(u)

22 ')'( uatask

taskkeuW


Applications of FPDs

• Pre-clinical imaging– Small animals

• Diagnostic imaging– Chest imaging– Breast imaging

• Image-guided interventions– Interventional radiology– IG radiation therapy– IG surgery

40

Control group

Ovariectomized group fed with regular food

Ovariectomized group fed with Ca-free food

Image courtesy of Dr. SY Lee’s Group, KHU






41

Image Courtesy of GE HealthCare






42

JM Park et al., Radiographics (2007)

Image Courtesy of Anrad


Pictures taken from M. Mahesh, Radiographics (2004)

"While cancer detection did not differ in woman screened with screen-film mammography or digital mammography, the recall rate and false-positive risk were lower with digital mammography than screen-film mammography …,"- M. Sala et al., Radiology, 2011






44

M Overdick, Philips, IWORID (2002)


Radiography is an overlaid shadow of 3D structures

45

H. Yun et al., NIMA in press (2011)

Duct network

Glandular tissue

Mass

Calcified duct

Microcalcifications


Energy discrimination: Duel-energy imaging

46

Low-KVp ILowIHighHigh-KVp

?ln ln lnx =WeightBone

High

BoneLow

Soft-tissue image

SoftLow

SoftHigh

Bone image


Depth discrimination: Cone-beam CT

48

서울삼성병원/국립암센터


Depth discrimination: Digital tomosynthesis

49

서울삼성병원


What is coming?

• To compete the conventional screen/film systems and/or CR systems– Should be mechanically robust & lighter: jet-printing (or digital lithography) onto flexible

substrates– Reduced cost: increased panel yield, use of cheaper scintillator (but the additional options e.g.,

tomosynthesis), digital lithography

• Towards low-dose imaging (or dynamic imaging)– Should be overcome electronic noise

• Direct conversion with new photoconductor• Amplifier per pixel• Avalanche gain

– Could be avoided Swank noise• Photon counting mode

50

a-Si:H active matrix gamma ray detectoron polyimide substrate

Image courtesy of TN Jackson, Penn. State Univ.

Y. El-Mohri, et al., Med. Phys. (2009)Collaborated with Xerox, PARC & dPix

SAPHIRE, W Zhao & JA Rowlands' Group


Photon-counting imaging

51

NIMA 607 (2009) 221-222

SNR: 1.59 vs. 0.25CNR: 8.93% vs. 0.9%


Integrating vs. counting

52

dN/dE

E

E

dN/dE

E

NSignal

Noise Swank

~N (Poisson)


• Gold standard for imaging neurovasculature and extremities

Post-injection image

Subtracted image

Motion artifacts in subtracted image

Pre-injection image

Digital subtraction angiography (DSA)

Y. Bentoutou et al., Pattern Recognition (2002)


Energy-resolved angiography (ERA)

54

J. Tanguay, H.K. Kim, I.A. Cunningham, in preparation

Photon Energy

# o

f Ph

oto

ns

water

Post-injection

Iodine

Photon Energy

# o

f Ph

oto

ns

Photon Energy

# o

f Ph

oto

ns

31 ;log2

1

jnN

Aj

j

j

Maximum-likelihood solution:

Average value of the linear mass-attenuationcoefficient for material and energy bin j


Signal-different-to-noise ratio

55


Truth

20

2

0

I

II AASDNR


Monte Carlo results

56


Non-subtracted

DSA ERA


Infinite dynamic range

57

J. Jakůbec, J. Instrum. (2008)


J. Jakůbec, J. Instrum. (2008)


Roentgen, revisited

59


Conclusions

• The x-ray has been revolved from analog to digital since the past 100 years, and maybe the next revolution would be happen through another 100-year time pass. However, small evolutions to improve the performance of DR detectors will be continued during the 100-year time pass.

• Additional work will be required to extend the cascaded linear-systems approach to deal with new technological developments and new detector designs.

• Although flat-panel detectors were introduced about three decades ago, the real war to replace film-screen or CR systems begins now and companies are up against stiff competition.

• For more information, please find:– HK Kim, IA Cunningham, Z Yin, and G Cho, “On the development of digital

radiography detectors : A review,” International Journal of Precision Engineering and Manufacturing, Vol. 9, No. 4, pp. 86-100 (2008). www.ijpem.org

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