Biomedical Engineering Reference
In-Depth Information
(e)
The presence of the catheter, the reticule, and the guide proves disad-
vantageous to the processing of the images
and to the evaluation of the
data by some procedure of images processing.
(f)
Impossibility of spatially locating the catheter.
The impossibility of lo-
cating the catheter with respect to a specific axis of coordinates makes
it impossible to make any attempt for three-dimensional representation
of the vessel only with the IVUS technique. For example, spatial location
of the effective section of the lumen and location of plaque and the re-
construction in the lengthwise direction of the vessel are still an open
problem of investigation [9].
(g)
Impossibility of evaluating dynamic parameters, different from the
single static characterization using the gray levels.
First achievements
are related to IVUS elastography [7] the purpose of which is to propose a
technique for tissue characterization.
The mentioned shortcomings are difficult to quantify and depend on the expe-
rience of the operator, that is he should have been trained in handling a large
number of patient cases. Some of the limitations of the IVUS technique can be
attenuated through algorithms of image processing; the limitations due to a sub-
optimal location of the borders of the arterial structure can be overcome with
new algorithms of segmentation. The question is how to develop robust algo-
rithms that can solve these problems, analyzing the artifacts with their multiple
appearances in IVUS images. Having a complete set of patient data to present all
variance of artifacts appearance in images would mean to dispose of a huge num-
ber of patient cases. A more efficient solution is to develop a simulation model
for IVUS data construction so that synthetic data is available in order to “train”
image processing techniques. In this way, different appearances of artifacts can
be designed to assure robust performance of image processing techniques.
Differences in IVUS data are caused not only by different morphological
structures of vessels but also by different parameters that influence the forma-
tion of IVUS images. The images depend on the IVUS apparatus calibration as
well as on interventional devices; small differences in parameters can lead to
a different gray-level appearance that can be interpreted in a different way by
physicians. A simulation model for IVUS data can help train the medical staff
as well as play an important role in designing and testing new interventional
