Full text: Close-range imaging, long-range vision

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REPRESENTING THE HUMAN VASCULAR SYSTEM 
WITH THE USE OF X-RAY PICTURES 
Á. Detrekói ^", K. Fekete *, Z. Tóth *, O. Alhusain *" *, A. Juhász^, I. Stuber ©, Á. Rakusz 
* BUTE, Department of Photogrammetry and Geoinformatics, Muegyetem rkp. 3. I. 19, H-1521 Budapest, Hungary (adetrekoi, 
; kfekete, attjuhasz)@epito.bme.hu, alhusain@eik.bme.hu 
MTA TKI, Geoinformatikai kutató csoport, Muegyetem rkp. 3. I. 19, H-1521 Budapest, Hungary 
* Semmelweis Medical Sciences University 
Commission V, WG V/3 
KEY WORDS: Close Range Photogrammetry, Medical Imaging, X-ray. 
ABSTRACT: 
In this paper, the determination of the measurements, shape and state of the human vascular system will be presented in detail. The 
determination process is done through creating and plotting the topology of the human vascular system. The images used in this 
project were, either collected by X-ray (róntgen) instrumentation or prepared by the correction of other imaging systems data. The 
measurements done in the digital domain were mostly done by the use of general-purpose image processing software. The 
measurements on the analogue images were done by the use of a monocomparator. For the displaying process, the split screen 
method was chosen to display the normalized stereo pair photos. This procedure was chosen because it satisfies the medical 
applications requirements for the need of displaying the plotting results onto various output instrumentation, and to assure wide 
range applicability for the system. 
1. INTRODUCTION 
During medical interventions to treat different illnesses, such as 
brain surgery operations, it is extremely important if not life 
saving, that the physician being able to know the dimensions 
and structure of the human organs and their vascular network. 
This exact knowledge about one human's organs can not be 
generalized because it varies from one individual to another 
making generalization in this regard associated with a good deal 
of error possibility. During our investigation of similar imaging 
methods like gamma cameras, computer tomography (CT), 
Magnetic renaissance (MR), and classic X-ray (róntgen) 
photography, we came to the conclusion that X-ray 
photography was one of the most suitable methods. The 
suitability of X-ray photography is due to its cost-effectiveness, 
availability of X-ray instrumentation and expert personnel, and 
the minimal intrusiveness associated with X-ray imaging. 
In our study, which is a joint research effort of the Department 
of Photogrammetry and Geoinformatics of Budapest University 
of Technology and Economics (BUTE) and Semmelweis 
Medical Sciences University (SMSU), the way of solving the 
above-mentioned task was done by the use of analogue and 
digital X-ray pictures. Object reconstruction which is 
mentioned few times in this project depends on Direct Linear 
Transformation (DLT) and was developed previously by our 
team. The following sections will present this research project 
in detail. 
2. THE PROPOSED SOLUTION 
2.1 Data collection and pre-processing 
During our work we had to solve the problem of placing the 
control points, which in case of differently arranged pictures 
ensure correct orientation possibilities. We have chosen a 
solution well known from X-ray photogrammetry, that is, we 
placed well-perceptible small metal balls on the plastic cassette 
  
* Corresponding author(s). 
holding the X-ray sensitive sheet at predetermined locations. 
Pinning ensured the fixation of the horizontal coordinates that 
are known from scale microscope measures. 
X-ray photographs generally suffer from two kinds of 
distortions inherently associated with X-ray imaging systems. 
These distortions are contrast distributions degradations and 
non-linearity distortions. Contrast distribution problems in 
medical imagery can be corrected easily by traditional 
sharpening filters such high-pass and high-boost filters 
(Gonzales and Woods, 1993). Non-linearity distortions can be 
corrected to an acceptable level by the use of 2-D interpolation 
(Alhusain, 2000). In the 2-D interpolation algorithm, a cell built 
on four neighbouring pixels is considered. The pixels are 
represented by their coordinates and grey levels. Two 1-D 
interpolations are carried out on the four pixels, two on each 
side of the cell, resulting in two interpolated values; another 1- 
D interpolation is carried out on the two previously interpolated 
values giving in the final 2-D interpolation result (Castleman, 
1996). 
2.2 Measurements and object reconstruction 
Measurements on the analogue photographs were done by the 
use of PK-1 monocomparator. In the case of digital images, a 
general purpose image processing system was used to measure 
the coordinates of different points (pixels) in the photographs. 
The accuracy of the measurements in relation to the digital 
photograph area was in the sub pixel range. Another 
measurement method, which substitutes the above mentioned 
procedure, is the 3-D plotting in the spatial model created by 
the normal stereo pair photographs. This last measurement 
procedure requires that the related points in the two 
photographs are identified and measured. In the measurement 
process we used a program developed by the Geodetic and 
Geophysical Research Institute of the Hungarian Academy of 
sciences. 
Because of the special structure of X-ray imaging systems, the 
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