DIGITAL CAMERAS AS LOW-COST TOOLS

FOR TELEMEDICINE AND E-HEALTH

Opportunities and Constraints

Vesselin Gueorguiev, Ivan Evg. Ivanov

Technical University Sofia, blvd. “Kliment Ohridski” 8, Sofia, Bulgaria

Desislava Georgieva

New Bulgarian University, Sofia, Bulgaria

Keywords: Image perception, Medical images, X-ray images.

Abstract: The aim of this paper is to present part of a research work oriented to selection and usage of low-cost

imaging devices for Telemedicine and e-Health. The results presented are oriented to increase the usability

of digital photo cameras as a device for creating and/or digitalizing medical images. All activities are part

of a DAPSEpro project “Medical data acquisition, processing and collection for e-Health solutions”.

1 INTRODUCTION

The aim of this paper is to present current results of

the DAPSEpro project “Medical data acquisition,

processing and collection for e-Health solutions” in

the part oriented to selection and usage of low-cost

imaging devices and following image processing for

the needs of telemedicine and e-Health. The present

work is the result of the partnership between the

Technical University of Sofia and the Medical

University Sofia (clinics of nephrology and

pulmonology).

2 MOTIVATION

Under the DAPSEpro project one of the initial tasks

was in the field of “digital libraries” and especially -

the need for digitalization and archiving of patients’

old X-rays. This provoked the development team to

design and implement a technology to solve this

problem.

Basic requirements and limitations for the

fulfilment of this task were:

 the ability to obtain 'acceptable' images from all

size classical X-ray pictures such as old X-rays,

badly preserved X-rays, or ones made on a

poorly

calibrated older generation machines

 very limited financial resources for new

equipment

 a quick and inexpensive image digitalization

process (Marketing research envisaged similar

services in prices between 5-15 USD depending on

the size and quality due).

Two possible solutions were investigated:

 usage of existing scanners for X-ray pictures or

scanners for semitransparent images

 design of specialized low cost system for X-rays

images digitalization.

To use existing scanners was impossible for the

following reasons:

 scanners, which can be used for all sizes of X-

rays at the required quality and speed, are too

expensive

 reasonably priced scanners have a number of

disadvantages:

o the scanning process is very-to-extremely slow

o any high quality scan needs unacceptably long

processing time

608

Gueorguiev V., Ivanov I. and Georgieva D..

DIGITAL CAMERAS AS LOW-COST TOOLS FOR TELEMEDICINE AND E-HEALTH - Opportunities and Constraints.

DOI: 10.5220/0003192906080613

In Proceedings of the International Conference on Health Informatics (HEALTHINF-2011), pages 608-613

ISBN: 978-989-8425-34-8

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

o pre-view and real scan are two different phases

and both are of long duration

 if the picture is bigger than 420x297 mm (format

A3) in any dimension the following problems

appeared:

o The picture has to be scanned in sections. This

requires adjustment of the picture section by

section to the axes of the scanner for the needs of

the stitching process. In practice this is not

absolutely possible or is very time-consuming,

requires skills and experience. In this case

stitching is mandatory. Because the scan process

is not automated stitching cannot be automated

either.

o In case when the top optical plane of the

scanner is under the top end of the scanner case

processing images bigger than A3 is impossible

because they have to be bent to follow the top

surface shape.

 only few scanners include a light intensity

control function

 a selected target zone of the picture cannot be

zoomed optically.

These observations directed our efforts to design

and implement a specialized scanning machine. The

first implementation used as a basis for new research

was a successful project implemented 10 year ago,

and it is still in operation in the Institute of

Orthopedics of the Medical University Sofia - a

system for handling X-ray images. Under this

project, together with colleagues from Sofia

University a system (a scanning device and software

for image processing) was designed and developed.

It is based on a digital video camera with high

optical zoom (20x) and black and white sensor with

an 800000 real pixels matrix. The success of this

solution proved the feasibility of low-cost solutions

based on modern digital photo- and video cameras.

The exploitation of the system revealed some

limitations, which were both the result of the quality

of the video cameras from that period, and the

peculiarities of the use by physicians:

Influence of the parameters of the optical system

and sensor matrix on the usability of the system,

differences in the perception of a digitalized X-ray

image and a classical X-ray film from medical point

of view; the limitations of the human eye and related

problems to achieve realism. These observations

accelerated our work significantly.

3 THE LIMITATIONS OF THE

HUMAN EYE:

HOW TO ACHIEVE REALISM

IN THE DIGITALIZATION

PROCESS

A major problem in using computers for image

visualization is the characteristics of the human

vision as a system for perceiving visual information:

in many aspects the human eye is an extremely

sensitive sensor, while for other things it is a very

imprecise one. This requires the use of special

computer visualization techniques targeted to the

application area: while with special effects for the

cinema the aim is to "trick" the eye while in

scientific visualization the goal is to increase the

perception and understanding of information.

One of the specifics of digital images as a basic

information source is that they have to be visualized

on many different types of output devices or media.

In present medical applications usually these are

different types of monitors and less often

reproduction on paper or film.

The sequence “image digitalization – image

visualization” generates new problems. Some of

them are:

 The terms “color space” and “color model”: the

color space represents the set of possible colors to

reproduce; the color model represents a method of

presentation of colors by a group of primary colors.

The color space of the human eye (known as CIE

1931 x,y chromaticity space – see Figure 1) is much

greater than that of any input and output digital

device. In addition, the color space of the digital

photo and video cameras (known as Adobe RGB) is

also greater than that of computer monitors (known

as sRGB). Additional sources of errors are

imprecisely (and/or wrongly) calibrated devices

(white point temperature characteristic). The white

point is the point of the color space and its incorrect

value moves along the line in the chart, i.e. moves

the device color space within the human eye

perception area. This changes the perception of

purity and color saturation which is inadmissible

when the color is the main source of information in

the image.

 One of the main problems in the image

perception is the perception of 'visual weight'. This

allows the perception of some parts and the

suppression of others, according to their location in

the image and the surrounding areas. For medical

DIGITAL CAMERAS AS LOW-COST TOOLS FOR TELEMEDICINE AND E-HEALTH

- Opportunities and Constraints

609

imaging this is particularly important because black

and white images are widespread: X-rays,

ultrasound and similar. An example is shown in

Figure 2 – scanned X-ray image and its negative.

 The human eye has an exponential law of

perception change depending on light intensity, i.e.

the sense of change for a color close to black and

another close to white is associated with a very big

difference in the change of intensity for both colors.

This could seriously change the perception of B/W

images particularly on the LCD-monitors, such as

laptops, as a function of the slope of the monitor.

For example, when one needs to observe white

details against a black background (figure 2a) the

optimal position is close to the perpendicular to the

view direction, while the opposite case (figure 2b)

requires a noticeably greater slope.

 The property of human vision, called

"Approximate color consistency", is another source

of very serious difference between classical

examination and the use of digital images. In nature,

when a human perceives two light sources as

equally white and they illuminate both sides of one

and the same object, the perception is the same color

of the two object sides. Shooting the same object by

digital camera has a different result: the color of the

object depends on the temperature of the light

source. The property of human vision, called

"Approximate color consistency", is another source

of very serious differences between direct

observation and the use of a digital image. In

medical applications this problem can be seen best

in the imaging and visualization of human skin.

Figure 1: CIE color space.

4 CAPABILITIES AND

LIMITATIONS OF DIGITAL

PHOTO CAMERAS

Modern digital photo cameras have a very high

potential, but the selection of an appropriate

apparatus is not a trivial task. It is necessary to

examine several key features and their mutual

influence on the shooting process. It is not rare that

individual characteristics of a good, but not user-

friendly digital camera require professional

photographic skills. It should be noted that the basic

requirements according to target area - color images

obtained for imaging (e.g. for the purposes of

dermatological remote diagnostic activities) or

digitalization of existing images are different.

When using color images there are two essential

characteristics: white balance and camera color

distortion. White balance directly affects the color

change because the temperature of the light source

affects the location of the ‘white point’ on the

“Equal Energy Curve” in color space. An incorrect

setting can result in the following side effects:

decolouring, bluish-green or reddish areas or spots.

These effects increase when shooting human skin

because of natural phenomena known as 'subsurface

scattering' and 'caustics'.

Color distortion is a feature of the cameras,

showing how natural color is perceived by the

camera when lighting is correct, i.e. shows a

replacement of natural color with a color from the

camera color space:

 digital cameras have completely different

characteristics, resulting from the combination of

lenses and an optic system, a sensor matrix and

embedded digital algorithms

 there are no cameras with equal color distortion

for different shooting modes for both single

shooting and video

 the setting for the film sensitivity (ISO value)

also affects the color distortion.

When the apparatus is used as a scanner the key

characteristics are: optical distortion (barrel or

pincushion); gray scale accuracy; sharpness, low

contrast details and resolution; embedded noise

reduction algorithms.

 The availability of optical distortion above 1% is

a limitation in the following cases:

o the use of images for measurement of lengths,

angles, distances, curves;

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o very big X-ray pictures and/or need to increase

the depth of the digital image requires scanning

in parts: in this case optical distortion prevents

the final stitch procedure;

o if a low level of distortion results from digital

processing by camera firmware no more than 2/3

of the image can be suitable for measurement or

stitch procedures.

 Digital cameras use a 3-channel (R, G, B) sensor

matrix. For B/W images these devices use digital

algorithms converting R-, G- and B-values for each

pixel in the intensity (gray colors): the type and

quality of the embedded algorithms specify the

correctness of the gray palette. In different shooting

modes and under different conditions, the gray

palette accuracy varies because the sensitivity of the

matrix color channels is changed differently.

 Digital cameras with excellent algorithms for

noise removal are suitable for laymen but from a

technical point of view their algorithms may distort

the realism of shooting images: some algorithms are

too aggressive, and as a result, small size details

disappear from the image.

 Sharpness, low contrast details and resolution

determine the level of detail that can be achieved in

different shooting conditions.

As a result of investigation and analysis of many

digital cameras and experiments with a number of

led to resulted to the following set of requirements:

 the camera should have a manual mode:

o After a stitch procedure the scanned image will

have the necessary quality and reliability only if

all parts are shot in the same mode and camera

settings.

o If color images are used to trace the growth of

some processes, the accuracy of the analysis and

results is determined by the camera settings for

each photo: different settings generate different

color distortion. As a result, one and the same

color in two images will result from two

different natural colors.

 the camera must ensure an adequate optical

zoom:

o scanning activities require minimum 10x

optical zoom, but the optimum is 12x or 14x

based on sensor matrix size

o if color images are used to trace the growth of

some processes the required optical zoom is

determined by the camera: one has to compare

the quality of images taken at close range with

no zoom, and those taken form a greater distance

and zoomed.

 Cameras with less than 7 million effective pixels

are useless. The scanning process requires 10 to 12

million effective pixels. Current cameras with more

than 14 million pixels are too noisy.

 Preferable cameras are those with least optical

distortion and chromatic aberration (“aberration”

means that some artefacts are added to the image).

 Cameras with weight less than 300 g require

much cheaper carrier mechanics for some activities.

A significant advantage is the ability to control and

manage the camera firmware externally. This

provides much greater flexibility and expands the

usability of the apparatus for the purposes of

Telemedicine and e-Health.

5 IMPLEMENTATION RESULTS

Two classes of digital photo cameras are used for

the development of camera-based scanning devices:

“Compact Super Zoom” (manual mode, 12x optical

zoom, 12 M effective pixels, less than 1% optical

distortion, <300 g) and „Compact” (manual mode,

4x optical zoom, 7 M effective pixels, ~ 1% optical

distortion, ~ 220 g). Cameras of the “Compact Super

Zoom” class have provided much greater

opportunities for developing devices which will

substantially expand the potential applications of the

system. All results described below are based on the

use of devices with this type of camera.

When using a digital camera as 'camera'

(creating images from nature) some new possibilities

are discovered:

 It is possible to create a model of image

transformation which allows the use of different

shooting settings when color images are used to

trace a growth. So far experiments have been

conducted only with the basic camera, but future

plans are to extend them to other digital photo

cameras.

 A method for using the captured image as a basis

to create a pseudo-3D image was developed. This

may improve the diagnostic possibilities when

additional information for texture is needed.

 The ability to manage firmware extremely

enhances the use of the digital photo camera. An

example is the possibility for direct capturing of

static and dynamic stereoscopic images. This will

allow remote obtaining of real three-dimensional

images.

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The results of using cameras as a scanner device

demonstrate the usefulness of this approach and also

that scanning with a resolution below grain size of

X-ray film is no longer a problem. This increases the

useful information, allowing digital processing to

eliminate errors in the final images (figures 3 and 4).

For X-rays having one of the following defects

(see figure 5) the developed technology significantly

increases perception (figure 6):

 X-ray images with overexposure

 X-ray images with underexposure

 Incorrectly treasured up X-ray images

 A badly calibrated X-ray machine: overexposure

and underexposure areas in one and the same image.

6 CONCLUSIONS

The images prepared and used for the present paper

were the ones used for diagnostic purposes and

served to confirm diagnoses made by other means.

Additionally it was confirmed that personnel with

lower qualification can easily interpret images.

Finally it was confirmed that images with very low

quality can be processed and interpreted. This

demonstrates the great potential of digital photo

cameras for Telemedicine and e-Health applications.

ACKNOWLEDGEMENTS

This work is funded by Bulgarian NSF under

D002/113-2008 and DRNF02/3-2009 projects.

REFERENCES

Dallas, William J. 1990 A digital prescription for X-ray

overload, IEEE Spectrum

Preim,B., Bartz, D., 2007 Visualization in medicine,

Morgan Kaufmann, ISBN 978-0123705969

Gallagher, Richard S., Computer Visualization: Graphics

Techniques for Engineering and Scientific Analysis,

Solomon Press, CRC Press LLC, ISBN 849390508

Stavitskii R.V. at al., 2006 An approach to decreasing

dose load in prophylactic X-ray examination,

Biomedical Engineering, Volume 40, Number 4 / July,

2006, pp. 191-193

a) positive (native) image

b) negative image

Figure 2: The “visual weight” can substantially change the

perception of details.

a) b)

c) d)

Figure 3: Some examples of image quality of scanned by

digital photo camera X-ray image.

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Figure 4: Different levels of details for scanned with

digital photo camera X-rays.

Figure 5: a) X-ray image with overexposure. b) Badly

calibrated X-ray machine.

Figure 6: a) Scanned X-ray image. b) details that can

be obtained after processing.

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