IMAGE QUALITY

IMAGE

Contrast

Resolution

Noise

Artifacts

Distortion

INTRODUCTION

- medical images for medical necessity (anatomical/ functional information)

- quality of medical image determined by:

* imaging method

* equipment characteristics

* imaging variables (transducers, coils, kV, gain,TE)

(* skills of operator and viewing condition)

Iterative reconstruction

* different imaging methods

* different equipment characteristics

* different equipment characteristics

* different imaging variables

* different imaging variables

80 kV 140 kV

Contrast

- difference in tissue caracteristics between specific points

low contrast medium high contrast

- result of a number of different steps during creation, image processing and image displaying

Contrast

• three main contributors:

1. Subject contrast- intrinsic factors- extrinsic factors

2. Detector (film) contrast

3. Displayed contrast (image reconstruction in digital radiograph, CT, MRI, PET,...)

Homogeneous Incident X-ray Beam

Patient

Detector

Profile of X-ray beam

emerging from patient

prior to reaching

detector

C= A-B/AA>B; C is 0,0-1,0 (1-100%)

A=N0e-mx and B=N0e

-m(x+z)

C = 1-e-mz

m attenuation coefficient

z thickness

1. Subject contrast

A=N0e-mx and B=N0e

-m(x+z)

C = 1-e-mz

m attenuation coefficient

z thickness

if z is larger or m is larger C is higher!

x-rays of low kV C is higher!

1. Subject contrast

- Intrinsic factors = actual anatomical or functional changes in the patient’s tissues, which give rise to contrast

Physical properties Physiological properties(f.e. atomic number) (f.e. metabolism)

•

1. Subject contrast

- Extrinsic factors = optimization of image-acquisition protocol to enhance subject contrast

Changing x-ray energy Contrast agent

1. Subject contrast

Changing TR i TE

2. Detector (film) contrast

2. Detector (film) contrast

3. Displayed contrast

- raw image information is processed into an image that is finallymeant for physician viewing

- medical images have bit depths ranging from 10, 12,14 bits(1024, 4096 to 16384 shades of gray)

- Modern displays capable of displaying 8-bit to 10-bit (256 to 1024shades of gray)

display computer needs to convert the higher bit depth data encoded on the image to the spectrum of gray scale on the monitor

lung window (W 1600/ C -600 H.U)

mediastinal window (W 350/ C 40 H.U.)

bone window (W 1600/ C 300 H.U.)

Resolution

- Spatial resolution in radiology refers to the ability of the imaging modality to differentiate two objects

Point Spread Function, PSF

= response of an imaging system to a point source

• most basic measure of resolution properties of an imaging system

• describes the extent of blurring that is introduced by an imaging system

• two-dimensional (2D) function PSF(x,y)

• Rotationally symmetric/ asymmetric

• describes the extent of blurring that is introduced by an imaging system

Point Spread Function, PSF= response of an imaging system to a point source

point source symmetric response of

„imaging system”

asymmetric response of

„imaging system”

Stationary Imaging System

- the PSF remains constant over the FOV of the imaging system

Nonstationary Imaging System

- has a different PSF depending on the location in the FOV

- assymetric system

Line Spread Function, LSF Edge Spread Function, ESF

Slit imaging in projection radiography Imaging a plane in tomographiy sytem

Image of Line

Profile of line is measuredperpendicular to the line

gaussian blur original increasing edge enhancement

Results of 2D image processing using a variety of different convolution kernels

G(x )=

H(x ') k (x-x ') dx ‘= H(x ) k(x )

LSF (x )=PSF (x, y) ⊗ LINE( y)

LSF x =

PSF x y dy

Modulation Transfere Function, MTF= spatial frequency response of an imaging system

• measures resolution in frequency domain(Fourier Transformation)

• measured in line pairs per millimeter (lp/mm)• limited by Nyquist limit

Modulation Transfere Function, MTF= spatial frequency response of an imaging system

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

Prostorna frekvencija (ciklus/mm)

10% MTF

limiting spatial resolution

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

MT

F(f

)

OUTPUTINPUT

Noise

= irregular granular pattern

- degrades image information (render images non-diagnostic)

- present in all electronic systems

- originates from a number of sources

Plain film

Plain film

Decreasing radiation intensity

CT

- Noise can be decreased by increasing mAs

- Noise can be decreased by changing filters during reconstruction

MRI

- main source is the patient's body (RF emission due to thermal motion)

- Noise can be decreased:

- use the correct coil and ensure that it is well tuned

- use a large FOV

- select thick slices

Artifacts

Medical images for medical necessity?

Department of Brain and Cognitive Sciences, MIT / Athinoula A.

Martinos Imaging Center at the McGovern Institute for Brain Research

Neuroscientist Rebecca Saxe captured an incredible image of herself holding her 2-month-old son, Percy, and it

may be the first image of its kind. She and her colleagues took the image simply because they wanted to see it, not

for any specific diagnosis or study.