Image Quality assessment in digital X-ray detection systems

AAPM 2004Summer School

Pittsburgh PA 29 July – 1 August

31-07-2004 Tom Bruijns / Dick Stueve Philips Medical Systems

Image Quality assessment in digital X-ray detection

systems

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Outline

- Introduction- Technologies in Rad and RF- Performance Characteristics- IQ assessment- IQ design: a system approach- Summary

- Evening session QC tools19:00-21:00

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Overview Digital Technologies

1970s 1980s 20001990s

1981First CR

1981Slit-scanchest unit

1992Se drumdetector

1977Digital

subtractionangiography

1997CCD-based

imaging

1997Se-basedflat-panel

1998CsI-basedflat-panel

Neitzel

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Overview Digital Technologies

CR in 1983

CR in 2004

~ 10-20x reduction in size and price

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Product range overview Digital Technologies

Rad systems:- Thoravision (selenium drum)- Computed Radiography- Flat Detector technology

RF systems- IITV technology (CCD based)- Flat detector to come

CV systems- IITV technology (CCD based)- Flat Detector technology

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Rad systems:- Thoravision- Computed Radiography- Flat Detector technology

RF systems- IITV technology (CCD based)- Flat detector to come

CV systems- IITV technology (CCD based)- Flat Detector technology

Product range overview Digital Technologies

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- Introduction- Technologies in Rad and RF- Performance Characteristics- IQ assessment- IQ design: a system approach- Summary- Evening session QC tools

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Flat Detector technology in Digital Radiography

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CR and DR

DR

CRCR :• DQE will increase• Line scan

Frost & Sullivan

CR will coexist next to DR for many years

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European ConsortiumThales, Philips, Siemens

ProductsStatic & Dynamic Flat x-ray Detectors (FD)

Trixell Moirans France

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Scintillator(CsI)

Amplifiers

A/D-Converter

a-Si SensorMatrix

AddressLines

Glass Plate

550 µµµµm thickness

Flat Detector Technology

43 cm x 43 cm static18 cm x 18 cm dynamic30 cm x 40 cm dynamic

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- For radiographic applications

- Cesium Iodide scintillator (600 µm)

- Amorphous silicon photodiode array

- Array size: 43 cm x 43 cm

- Pixel size: 143 µm

- Bit depth:14 bits

- Image matrix: 3k x 3k

- Low noise electronics

- High sensitivity

Large area (43 cm x 43 cm) 9 Mpixel Flat Detector

43 cm 43 cm

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- For vascular (and RF) applications





- Bit depth:14 bits

- Image matrix: 2.5 k x 2 k


- High sensitivity

5 Mpixel Dynamic Flat Detector

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- For cardio and vascular applications





- Bit depth:14 bits

- Image matrix: 1 k x 1 k


- High sensitivity

1 Mpixel Dynamic Flat Detector

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CCD based IITV technology for RF applications

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- Used for dynamic applications

- II: Cesium Iodide scintillator

- II size: 38 cm diameter

- Up to 5 zoom fields

- CCD Pixel size: 12,8 µm

- CCD Full well capacity: 170 ke-

- CCD read out noise 40 e-

- Bit depth:12 bits

- Image matrix: 10242

CCD based IITV technology for RF applications

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FD technology versus CCD based IITV technology for RF applications

+ No vignetting & no distorsion for FD

+ High resolution + coverage

+ High DQE for FD

+ Flat

- Price level high for FD

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Image Quality Triangle

DQE(f)

Resolution

ContrastNoise,dose,

spectrum

NPS(f)MTF(f)

SNR(f)Neitzel, Malmö 2004

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- Bit depth:14 bits



- High X-ray sensitivity


43 cm 43 cmLow noise

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- Bit depth:14 bits



- High sensitivity


43 cm 43 cmResolution

(and Coverage)

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- For dynamic applications






- Low dark noise 40 e-

- Bit depth:12 bits


CCD based IITV technology for RF applicationsLow

Noise

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- For dynamic applications






- Bit depth:12 bits


CCD based IITV technology for RF applicationsResolution

(and coverage)

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Image Quality Triangle

DQE(f)

Resolution

ContrastNoise,dose,

spectrum

NPS(f)MTF(f)

SNR(f)Neitzel, Malmö 2004

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Detective Quantum Efficiency

The detective quantum efficiency (DQE) is considered to be the fundamental performance parameter of digital X-ray detectors.

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There are many ways to come to many different answers

But

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Working group FD (DR)IEC standard 62220-1

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Neitzel, Günther-Kohfall, Borasi, SameiMedical Physics August 2004


3 methods for analysing 1 dataset

Differences +/- 15%

After using standardIEC 62220-1

Differences +/- 5%

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Linking DQE and observer tests

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DQE versus EAK for dynamic 30x40 FD and IITV

DQE (@ low spatial frequency) versus EAK

0

20

40

60

80

100

1 10 100 1000 10000

EAK [nGy]

DQ

E (l

f)

FD

IITV

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Observation tests (using Treshold Contrast Detail Detectability)

AACAH

tt ×

=)(1

)(

A

)(AHt

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Observation tests IITV (L) and FD (R)

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Observation tests IITV and FD

0.9 uGy

1

10

100

0.1 1 10

SQRT (A)

Ht(A

)

3.5 uGy

1

10

100

0.1 1 10

SQRT (A)

Ht(A

)

---- FD

---- IITV

High dose

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TCDD versus EAKHt(max) versus EAK

10

100

0.1 1 10

EAK [ uGy ]

Ht(

max

)

FD

II

Ht(max) versus EAK

1

10

100

1 10 100

EAK [nGy]

Ht(

max

)

FDII

DQE (@ low spatial frequency) versus EAK

0

20

40

60

80

100

1 10 100 1000 10000

EAK [nGy]

DQ

E (l

f)

FD

IITV

DQE versus EAK

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Rationale of Image Quality (IQ) Model (Kroon)

- IQ analysis of (non-)existing systems- system (de)composition for design process- comparison of present versus future systems

- Fast acquisition of IQ characteristics- optimization requires extensive data amount- simulation (seconds) versus experiment (hours-days)

- Various IQ related studies- design of test objects and methods

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• Combines the IQ requirements of components into system level IQ specification

• All IQ main items are analyzed simultaneously, leading to a.o. DQE

• Permits tolerance and parameter studies• Allows optimisation and prevents sub-optimisation• Design of test objects & methods

Objectives of Image Quality (IQ) Model

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Image Quality Model Main Items

- X-radiation spectrum, dose, AEC

- Contrast range and transfer

- Sharpness MTF of stationary object

- Motion blur MTF of moving object

- Noise dynamic & structure WS

- Mixed geometrics & cosmetics

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- Model input:- Components- Configuration- Tuning

- IQ model:- Architecture- IP functions

- Model output- IQ descriptors

Sinar-X

��

��

��

� ��

��

��

��

��

X-rayEnergy

Spectrum

IntensityTransferFunction

ModulationTransferFunction

WienerSpectrum

TemporalMTF

Input → Image Quality Model → Output

IQ model

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Image Quality Model Implementation

- PC with LabVIEW ®- Visual programming- Clear hierarchy- IQ analysis << 1 sec- 350 program parts- About 300 variables for

settings, UI and system definition

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Summary

We discussed:

- Products FD and IITV and their proporties- DQE and the present limitations- DQE versus observation tests- IQ modeling for fully optimized system IQ

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Thank you for your attention

See you this evening at our booth

for the session “QC tools”

Tom BruijnsDick Stueve

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Image Quality assessment in digital X-ray detection systems

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