Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 1

Digital image self-adaptive acquisition in medical x-ray imaging

Bao Jie, Gao Jun et.al.Lab on Image Information Processing

Hefei University of Technology , China

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 2

Content

What is X-ray fluoroscopy system and digital acquisition systemThe principle and implementation of self-adaptive digital acquisition

Experiment and Conclusions

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 3

1. What is X-ray fluoroscopy system and digital acquisition

system?

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 4

What’s X-ray fluoroscopy system?

X-ray fluoroscopy system is a system formedical diagnosing that can render image ofthe body of patient by convert X-ray whichpass through and attenuated by the body intovisible light and record it on film or othermedia. It’s a very common method forexamination in hospitals.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 5

Construction of X-ray fluoroscopy system

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 6

Why study the digital acquisition of X-ray fluoroscopy system?(1)

The digitalization of x-ray imaging is very important for PACS (Picture Archiving and Communication system); high-quality digital X-ray medical images are indispensable for PACS data source.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 7

Why study the digital acquisition of X-ray fluoroscopy system?(2)

There are three ways to digitalize x-ray imaging

Computed Radiography (CR)

Digital Radiography (DR)

Video digital acquisition.

Advantages of video digital acquisition : ability to see dynamic change of organs, device simplicity, operating convenience, and low-cost

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 8

The main difficulties in video digital acquisition

x-ray fluoroscopy image detection noise and digital quantum noiseAdjusting imaging contrast and resolution

Device background signal

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 9

How to deal with them?

Improve hardware quality of x-ray imaging system

Choose grabber board with high quantization precision

Voltage stabilization and electromagnetic shielding

choose a appropriate working point automatically and suppressed background signal by software

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 10

x-ray video NSPgrabber board Host

Control

PACS

Enhancement

Annotation

Display

Diagnosemanual

Informationnavigation

Report

Aided diagnose

Aided treatment

Archiving and backup

Query and management

Digital video processing system(1)

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 11

Digital video processing system(2)

Host should analyze the input signal while sampling and quantization to adjust grabber board setting for valid signal to utilize the dynamic range sufficiently, and to make device working in linear range.

The grabber board we used is NSP (Native Signal Process) frame-grabber board DT3153-LS, it can adjust reference, offset, gain, black level and white level by software, which make it possible for self-adaptive acquisition by software.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 12

2. The principle and implementation of self-adaptive

digital acquisition

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 13

Self-adaptive digital acquisition

To resolve problems brought forward in section 1, we use digital subtraction technique to realize background removing for self-adaptive acquisition, and monitor the dynamic range of image valid region to search for the best acquisition working point automatically.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 14

Self-adaptive digital acquisition system

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 15

3.1Valid region recognition

The acquired image is not entirely valid. Generally speaking, the valid region is a circle.

We should only count on valid region while removing background and analyzing the image feature to adjust acquisition parameters, so we must recognize the valid region at first.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 16

(a) Whole valid observeregion. White line isdetected region edge byimproved seed algorithm.

(b) Valid observe region with occlusion

Valid observe region

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 17

Valid region detection algorithm (1)

1． Compute the histogram of left and right narrow edges of the image, the gray-level corresponding to histogram peak value is the gray-level of invalid region.

2. Perform median filtering to remove noise.

3. Grow region using classical seed growing algorithm starting from any invalid point.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 18

Valid region detection algorithm (2)

4. Generate initial mask(bilevel ) image of valid region. Perform Sobel operator to this image to extract its edge.

5. Detect circle by general Hough transform; get the radius and the center of the circle.

6. Generate valid region mask using result of step 5.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 19

3.2 Background removing

Nonuniform background will affect image quality and the computing of image characteristic to adjust acquisition parameters.

So a digital subtraction will remove background signal while keep the validity of information.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 20

Background removing algorithm

1. Acquire and save device background signal (I1) when device is idle.

2. Acquire images to be observed (I2).

3. Perform image operation in valid region : I3=I1-I2 ; I4=NOT I3;

4. I4 is the image signal removed of background.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 21

After above-mentioned pre-processing, we will adjust black level, white level, gain, reference and offset automatically based on histogram analysis of image valid region to obtain best acquisition quality. Black level = - offset

White level = reference / gain -offset

3.3 Setting acquisition working point

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 22

Meaning of offset, gain and reference

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 23

Meaning of black level and white level

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 24

Decreasing offset will shift image to light zone, increasing offset will shift image to dark zone, namely offset behaves as brightness adjusting; decreasing reference will compress image to light zone, increasing reference will compress image to dark zone, namely reference behaves as contrast adjusting.

Working point setting rule

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 25

Analyze the proportion of dark zone and light zone in the histogram of image valid region, the aim of adjusting is to keep proper proportion of dark zone and light zone for best image acquisition performance.

Setting brightness at first to ensure dark zone isn't too much then setting contrast( that is, properly setting white level by adjusting reference).

Dynamic range analysis of valid region

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 26

Self-adaptive acquisition parameters setting

B e g i n R e a d i n e s s j u d g m e n t

I m a g e a c q u i s i t i o n V a l i d r e g i o n r e c o g n i t i o n , b a c k g r o u n d r e m o v i n g

V a l i d r e g i o n a n a l y s i s D y n a m i c

T o o d a r k r a n g e

T o o b r i g h t W h i l e ( d a r k z o n e i s t o o m u c h & & o f f s e t

i s n o t o u t o f l o w e r b o u n d ) W h i l e ( d a r k z o n e i s t o o f e w & & o f f s e t i s

n o t o u t o f u p p e r b o u n d ) D e c r e a s e o f f s e t I n c r e a s e o f f s e t

I m a g e a c q u i s i t i o n , b a c k g r o u n d r e m o v i n g

I m a g e a c q u i s i t i o n , b a c k g r o u n d r e m o v i n g

V a l i d r e g i o n a n a l y s i s

V a l i d r e g i o n a n a l y s i s L i g h t

L e s s z o n e a n a l y s i s

M o r e W h i l e ( l i g h t z o n e i s t o o m u c h & &

r e f e r e n c e i s n o t o u t o f u p p e r b o u n d ) W h i l e ( l i g h t z o n e i s t o o f e w & &

r e f e r e n c e i s n o t o u t o f l o w e r b o u n d ) D e c r e a s e r e f e r e n c e I n c r e a s e r e f e r e n c e

I m a g e a c q u i s i t i o n , b a c k g r o u n d r e m o v i n g

I m a g e a c q u i s i t i o n , b a c k g r o u n d r e m o v i n g

V a l i d r e g i o n a n a l y s i s

V a l i d r e g i o n a n a l y s i s

E n d

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 27

It's very inefficient and unnecessary to setting best working point every time we take fluoroscopy.

In practice, expert judgment and adjusting is used to choose universal acquisition parameters.

Universal acquisition parameters choosing

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 28

3. Experiment and Conclusions

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 29

Run interface of self-adaptive acquisition module

Run interface of self-adaptive acquisition module in ImagePro™ implemented by Visual C++6.0

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 30

Valid region detection

Original Image Valid region mask image Sobel edge-detect image

integrated valid region Rim of Valid Region by improved algorithm

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 31

Background removing

acquired image with nonuniform background

device background signal

image after removing device background

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 32

self-adaptive adjusting(1):

Acquired image before self-adaptive adjusting. Black level=0V, white level =0.7V, offset=0V, gain=1, reference =0.7V

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 33

self-adaptive adjusting(2):

Histogram of valid region in (1). mean = 70.48, median value=54. Image is too dark.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 34

self-adaptive adjusting(3):

Acquired image after self-adaptive adjusting. Black level =-0.042V, white level =0.258V, offset=0.042V, gain=2, reference= 0.6V

scapula

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 35

self-adaptive adjusting(4):

Histogram of valid region in (3). mean = 121.19． median value = 113.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 36

Conclusions

It's possible to implement self-adaptive acquisition of medical video image automatically by integrating various images processing method. The proposed method has recognized the valid region of image and removed the background, then adjusted acquisition parameters by analyzing image dynamic range to obtain best acquisition quality. But there still some problem remained to be resolved.

Aug.22,2000,WCC2000 Jie BAO , ImageInfoLab , Hefei University of Technology 37

Thank you!