Medical Imaging. Politechnika Łódzka, ul. śeromskiego 116, Łódź, tel. (042)

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Lech Romanowski
6 lat temu
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Prezentacja multimedialna współfinansowana przez Unię Europejską w

Innowacyjna dydaktyka bez ograniczeń - zintegrowany rozwój

edukacyjna i wzmacniania zdolności do zatrudniania osób

1 Prezentacja multimedialna współfinansowana przez Unię Europejską w ramach Europejskiego Funduszu Społecznego w projekcie pt. Innowacyjna dydaktyka bez ograniczeń - zintegrowany rozwój Politechniki Łódzkiej - zarządzanie Uczelnią, nowoczesna oferta edukacyjna i wzmacniania zdolności do zatrudniania osób niepełnosprawnych Politechnika Łódzka, ul. śeromskiego 116, Łódź, tel. (042)

2 Quality of medical images 2 Lecture overwiev: Definition of image quality Main factors influencing the quality unsharpness contrast noise distorsions and artifacts Qauntitative assessment of the image quality

3 Image quality The purpose of medical image: 3 treatment monitoring detection disease or injury treatment determination of its nature diagnosis The degree to which the image achieves its purpose is considered as image quality

4 Image quality 4 image clarity image quality correct areas of the patient appropriate imaging technique detectability of given disease/injury A measure of how well information of interest (about the anatomy, physiology, functional capacity) is displayed in an image

5 Image clarity 5 unsharpness image noise image clarity contrast distorsions & artifacts

6 Unsharpness 6 geometric receptor unsharpness subject motion U = U g +U s +U m +U r

7 Geometric unsharpness 7 U g1, d 1 U g2, d 2 d 1 >d 2 => U g1,>u g2

8 Subject unsharpness 8

9 Motion unsharpness 9 Anatomic structure Speed [mm/s] Head 1-2 Upper abdomen Lower abdomen Lungs ( ) Heart muscle ( )

10 10 Receptor unsharpness Introduced by the process, which converts the data acquired by given visualisation technique into an image matrix: 192x192 FOV: 400x400 mm matrix: 96x96 FOV: 400x400 mm matrix: 64x64 FOV: 400x400 mm

11 Image contrast 11 intristic receptor contrast imaging technique contrast agent Contrast describes the ability of distinguishing of subtle features (details) in the object

12 Intristic (subject, object, patient) contrast 12 Radiography Physical density Atomic number Nuclear medicine Ultrasound Computed Tomography Activity Velocity Physical density Distribution Acoustic impedance Electron density Magnetic Resonance Proton density Thickness Thickness Flow Flow Relaxation times Represents the difference in physical composition of visualised structures

13 Imaging technique 13 T1 T2* T2* T2 Different MR acquisition protocols (sequences)

14 Contrast agents 14 MR Venography Contrast echocardiogram Left kidney (MR, gadolinium)

15 Receptor contrast 15 Depends on properties of image converting/displaying devices Brightness 1 B = MN M N i= 1 j= 1 M N 1 2 Contrast C = [ f ( i, j) B] MN J=194, C=29 i= 1 j= 1 f ( i, j) J=112, C=47 J=29, C=38

16 Distorsions & artifacts 16 Caused e.g. by image formation system (optical), unequal amplification (radiography), non-uniform magnetic field (MR), multiple echos (ultrasound), Barrel Multiple echo Unequal amplification Ringing

17 Image noise 17 Gaussian noise n g (x) = 1 2πσ 2 e ( x µ ) 2 2σ 2 n r (x) = x ( x 2 ν 2 ) xν σ e 2σ 2 I 0 σ Rician noise (MR)

18 Image noise 18 Pulse noise (random distribution of maximal & minimal intensities) Pulse noise in CCD matrix

19 Image degradation model 19 Source image Degraded image distorsion η(x,y) g(x,y) H(.) + f(x,y) ( ) = H g( x, y) f x, y [ ]+η x, y ( )

20 Signal to noise ratio Signal-to-noise ratio (SNR or S/N) is a quantitative measure of image quality, it estimates how much an image has been corrupted by

20 20 Signal to noise ratio Signal-to-noise ratio (SNR or S/N) is a quantitative measure of image quality, it estimates how much an image has been corrupted by noise. SNR = P( f ) P(n) SNR db =10log 10 P( f ) P(n) SNR in practice: SNR = µ signal 2 σ noise ROIs for estimation of µ signal ROIs for estimation of σ noise

21 Image restauration 21 σ η σ f original image degrdation + noise result of Wiener filtering (1) Wiener filtering K=σ η /σ f

22 Point Spread Function (PSF) 2 x + y h( x, y ) = exp 2 2σ Image formation model 2 (x,y) 22 Image plane of the imaging sensor f(x,y) 3D x g(α,β) (α,β) ( ) = g( α,β) f x,y h( x,y,α,β)dα dβ h(.) is termed the point spread function of the imaging system; it describes its response to a point source.

23 Point Spread Function (PSF) 23 PSF is a measure of a minimum distance between two objects when they can be clearly distinguished in the image closer structures are interpreted as a single image objects their boundaries overlap

24 Modulation Transfer Function 24 F(u,v) = G(u,v)H(u,v) MTF is a Fourier transform of PSF. It represents a frequency characteristics of the imaging system. H( u,v) = F[ h(x,y) ]

25 25 Modulation Transfer Function MTF dpi MTF dpi

26 26 Modulation Transfer Function MTFs of radiographic imaging system: A)screen-film B)image formation system C)object motion D)resulting function for the entire system frequency [Hz]

27 Prezentacja multimedialna współfinansowana przez Unię Europejską w ramach Europejskiego Funduszu Społecznego w projekcie pt. Innowacyjna dydaktyka bez ograniczeń - zintegrowany rozwój Politechniki Łódzkiej - zarządzanie Uczelnią, nowoczesna oferta edukacyjna i wzmacniania zdolności do zatrudniania osób niepełnosprawnych Politechnika Łódzka, ul. śeromskiego 116, Łódź, tel. (042)

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