uiawf2009.bib

@inproceedings{muehl_computer_2009,
author = {Judith Muehl and Bernhard Kainz and Rupert Portugaller and Philipp
Stiegler and Christian Bauer},
title = {Computer oriented image acquisition of the liver: Toward a better
numerical model for radiofrequency ablation},
booktitle = {Proc. {IEEE} Engineering in Medicine and Biology Society {(EMBC)}},
year = {2009},
pages = {3755--3758},
address = {Minneapolis, {MN}},
publisher = {{IEEE} {EMBS}},
abstract = {Simulating physiological interventions for planning purposes requires
an accurate virtual liver model as computation input. To best meet
the demands the data acquisition has to be oriented on image processing
purposes. We provide a {CT} imaging protocol which makes it possible
to extract much more vessels with the same algorithms than when using
them on data sets from the clinical routine. Medical evaluation of
physiological models demand a statistical evaluation in a pre-clinical
study, that means in a first step reproducible results for a large
number of subjects. So data acquisition should be as automatic as
possible without neglecting modeling demands. Image quality should
be reproducible to guarantee an ongoing high quality of image processing
results. Our imaging protocol allows in best case an automatic processing
of images for extracting clearly the liver surface and all three
vessel trees. We evaluate that protocol with several experiments
on pigs where we can demonstrate a segmentation of typically ten
times more vessels than for standard data sets from clinical routine.
For the post processing of the image volumes two recently published
techniques are combined to gain optimal results.}
}