<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tobias Heimann</style></author><author><style face="normal" font="default" size="100%">Brahm Van Ginneken</style></author><author><style face="normal" font="default" size="100%">Martin A Styner</style></author><author><style face="normal" font="default" size="100%">Yulia Arzhaeva</style></author><author><style face="normal" font="default" size="100%">Volker Aurich</style></author><author><style face="normal" font="default" size="100%">Christian Bauer</style></author><author><style face="normal" font="default" size="100%">Andreas Beck</style></author><author><style face="normal" font="default" size="100%">Christoph Becker</style></author><author><style face="normal" font="default" size="100%">Reinhardt Beichel</style></author><author><style face="normal" font="default" size="100%">György Bekes</style></author><author><style face="normal" font="default" size="100%">Fernando Bello</style></author><author><style face="normal" font="default" size="100%">Gerd Binnig</style></author><author><style face="normal" font="default" size="100%">Horst Bischof</style></author><author><style face="normal" font="default" size="100%">Alexander Bornik</style></author><author><style face="normal" font="default" size="100%">Peter MM Cashman</style></author><author><style face="normal" font="default" size="100%">Ying Chi</style></author><author><style face="normal" font="default" size="100%">Andres Córdova</style></author><author><style face="normal" font="default" size="100%">Benoit M Dawant</style></author><author><style face="normal" font="default" size="100%">Márta Fidrich</style></author><author><style face="normal" font="default" size="100%">Jacob D Furst</style></author><author><style face="normal" font="default" size="100%">Daisuke Furukawa</style></author><author><style face="normal" font="default" size="100%">Lars Grenacher</style></author><author><style face="normal" font="default" size="100%">Joachim Hornegger</style></author><author><style face="normal" font="default" size="100%">Dagmar Kainmüller</style></author><author><style face="normal" font="default" size="100%">Richard I Kitney</style></author><author><style face="normal" font="default" size="100%">Hidefumi Kobatake</style></author><author><style face="normal" font="default" size="100%">Hans Lamecker</style></author><author><style face="normal" font="default" size="100%">Thomas Lange</style></author><author><style face="normal" font="default" size="100%">Jeongjin Lee</style></author><author><style face="normal" font="default" size="100%">Brian Lennon</style></author><author><style face="normal" font="default" size="100%">Rui Li</style></author><author><style face="normal" font="default" size="100%">Senhu Li</style></author><author><style face="normal" font="default" size="100%">Hans-Peter Meinzer</style></author><author><style face="normal" font="default" size="100%">Gábor Németh</style></author><author><style face="normal" font="default" size="100%">Daniela S Raicu</style></author><author><style face="normal" font="default" size="100%">Anne-Mareike Rau</style></author><author><style face="normal" font="default" size="100%">Eva M Van Rikxoort</style></author><author><style face="normal" font="default" size="100%">Mikael Rousson</style></author><author><style face="normal" font="default" size="100%">László Ruskó</style></author><author><style face="normal" font="default" size="100%">Kinda A Saddi</style></author><author><style face="normal" font="default" size="100%">Günter Schmidt</style></author><author><style face="normal" font="default" size="100%">Dieter Seghers</style></author><author><style face="normal" font="default" size="100%">Akinobi Shimizu</style></author><author><style face="normal" font="default" size="100%">Pieter Slagmolen</style></author><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Grzegorz Soza</style></author><author><style face="normal" font="default" size="100%">Ruchaneewan Susomboon</style></author><author><style face="normal" font="default" size="100%">Jonathan M Waite</style></author><author><style face="normal" font="default" size="100%">Andreas Wimmer</style></author><author><style face="normal" font="default" size="100%">Ivo Wolf</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison and evaluation of methods for liver segmentation from CT datasets</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE TRANSACTIONS ON MEDICAL IMAGING</style></secondary-title><short-title><style face="normal" font="default" size="100%">IEEE T MED IMAGING</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug 2009</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Price, K., Anything you can do, I can do better (no you can't) (1986) Comput. Vis. Graph. Image Process, 36 (2-3), pp. 387-391;S. G. Armato, G. McLennan, M. F. McNitt-Gray, C. R. Meyer, D. Yankelevitz, D. R. Aberle, C. I. Henschke, E. A. Hoffman, E. A. Ka</style></pub-location><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">1251 - 1265</style></pages><isbn><style face="normal" font="default" size="100%">0278-0062</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the &quot;MICCAI 2007 Grand Challenge&quot; workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was provided to train and tune algorithms in advance. Participants were also allowed to use additional proprietary training data for that purpose. All teams then had to apply their methods to 10 test datasets and submit the obtained results. Employed algorithms include statistical shape models, atlas registration, level-sets, graph-cuts and rule-based systems. All results were compared to reference segmentations five error measures that highlight different aspects of segmentation accuracy. All measures were combined according to a specific scoring system relating the obtained values to human expert variability. In general, interactive methods reached higher average scores than automatic approaches and featured a better consistency of segmentation quality. However, the best automatic methods (mainly based on statistical shape models with some additional free deformation) could compete well on the majority of test images. The study provides an insight in performance of different segmentation approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques. © 2009 IEEE.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><work-type><style face="normal" font="default" size="100%">Journal article</style></work-type><notes><style face="normal" font="default" size="100%">ScopusID: 68249121543doi: 10.1109/TMI.2009.2013851</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Emese Balogh</style></author><author><style face="normal" font="default" size="100%">Anna Vilanova Bartroli</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Franz Lindbichler</style></author><author><style face="normal" font="default" size="100%">Andrea Ruppert</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Emanuele Neri</style></author><author><style face="normal" font="default" size="100%">Davide Caramella</style></author><author><style face="normal" font="default" size="100%">Carlo Bartolozzi</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Techniques of Virtual Dissection of the Colon Based on Spiral CT Data</style></title><secondary-title><style face="normal" font="default" size="100%">Image Processing in Radiology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin</style></pub-location><pages><style face="normal" font="default" size="100%">257 - 268</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Colorectal cancer represents the third most commonly diagnosedcancer and is the second leading cause of cancer deaths in the United States (Gazelle et al. 2000). In addition, colorectal cancer is responsible for about 11% of all new cancer cases per year (Gazelle et al. 2000). Five-year prognosis is about 90% for patients with localized disease compared to 60% if there is a regional spread and a drop to 10% in patients with distant metastasis (Gazelle et al. 2000). In the field of medicine there is a widely accepted opinion that most colorectal cancers arise from pre-existent adenomatous polyps (Johnson 2000). Therefore, different societies, such as the American Cancer Society, have proposed screening for colorectal cancer (Byers et al. 1997; Winawer et al. 1997). Today, different options exist for detection of colorectal cancer, including digital rectal examination, fecal occult blood testing, flexible and rigid sigmoidoscopy, barium enema and its variants, colonoscopy and recently computed tomography or magnetic resonance-based virtual colonography (Gazelle et al. 2000).&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Book chapter</style></work-type><notes><style face="normal" font="default" size="100%">doi: 10.1007/978-3-540-49830-8_18</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Darius Mohadjer</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">Franz Lindbichler</style></author><author><style face="normal" font="default" size="100%">Bernhard Geiger</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Walter Hruby</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">New advances for imaging laryngo / trachealstenosis by post processing of spiral-CT data</style></title><secondary-title><style face="normal" font="default" size="100%">Digital (r)evolution in radiology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Wien; New York</style></pub-location><pages><style face="normal" font="default" size="100%">297 - 308</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Darius Mohadjer</style></author><author><style face="normal" font="default" size="100%">Franz Lindbichler</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">Bernhard Geiger</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Cornelius T Leondes</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Techniques in 3D Assessment of Tracheal-Stenosis by the Mean of Spiral Computed Tomography (S-CT) and Their Applications</style></title><secondary-title><style face="normal" font="default" size="100%">Medical Imaging Systems Technology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">World Scientific</style></publisher><pub-location><style face="normal" font="default" size="100%">Singapore</style></pub-location><pages><style face="normal" font="default" size="100%">61 - 80</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Endotracheal intubation is the most common cause of Laryngo-Tracheal Stenoses (LTS), followed by trauma and prior airway 
surgery.1–3 In rare cases LTS may have resulted also from 
inhalation injuries, gastro-esophageal reflux disease, neoplasia 
and autoimmune diseases like Wegeners granulomatosis or 
relapsing polychondritis.1,4 In pediatric patients vascular 
compression of the trachea is a common cause of tracheal 
indentations.5 Clinical management of these conditions requires 
information on localization, grade, length and dynamics of the 
stenosis. Exact LTS information is necessary, since stenoses 
with a length less than 1.0 cm can be treated by an endoscopic 
surgery.6,7 Besides Fiberoptic Endoscopy (FE), which represents 
the gold standard for airway evaluation, imaging modalities like 
conventional radiography, fluoroscopy, tracheal tomograms, 
Magnetic Resonance Imaging (MRI) and above all Spiral Computed 
Tomography (S-CT) are an essential part of the clinical work.1,8 
S-CT and the recent introduction of multislice imaging allows 
volumetric data acquisition of the Laryngo–Tracheal Tract (LTT) 
during a short time span. Decreased motion artifacts and 
increased spatial resolution form the basis for high quality 
post processing.9,10 The improved performance of today's 
workstations permits the use of sophisticated post processing 
algorithms even on standard hardware like personal computers. 
Thus real time 3D display and virtual endoscopic views (virtual 
endoscopy) are just one mouse click away. Other algorithms 
compute the medial axis of tubular structures like airways or 
vessels in 3D, which can be used for the calculation of 3D cross 
sectional profiles for better demonstration of caliber 
changes.11 Thus display of S-CT axial source images is moving 
rapidly to 3D display. Moreover, established network connections 
within and between institutions allows telemedical cooperation. 
Web technologies offer an easy to use way for information 
exchange. The objective of this paper is to present an overview 
on 3D display and quantification of LTS as well as to provide 
information how these results can be presented and shared with 
the referring physicians on the hospitals computer network. This 
article is structured in seven parts; namely: S-CT data 
acquisition for LTS imaging; selected 3D image post processing 
algorithms; 3D display; Virtual endoscopy; Objective LTS degree 
and length estimation using LTT 3D — cross-sectional profiles; 
Intranet applications; and a conclusion is drawn in the final 
section.
</style></abstract><notes><style face="normal" font="default" size="100%">doi: 10.1142/9789812701077_0003</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Reinhardt Beichel</style></author><author><style face="normal" font="default" size="100%">Thomas Pock</style></author><author><style face="normal" font="default" size="100%">Christian Janko</style></author><author><style face="normal" font="default" size="100%">Roman B Zotter</style></author><author><style face="normal" font="default" size="100%">Bernhard Reitinger</style></author><author><style face="normal" font="default" size="100%">Alexander Bornik</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Georg Werkgartner</style></author><author><style face="normal" font="default" size="100%">Horst Bischof</style></author><author><style face="normal" font="default" size="100%">Milan Sonka</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">J Michael Fitzpatrick</style></author><author><style face="normal" font="default" size="100%">Milan Sonka</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Liver segment approximation in CT data for surgical resection planning</style></title><secondary-title><style face="normal" font="default" size="100%">Medical Imaging 2004: Image Processing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2004///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">SPIE</style></publisher><pub-location><style face="normal" font="default" size="100%">Bellingham; WashingtonScheele, J., Anatomical and atypical liver resection (2001) Chirurg, 72 (2), pp. 113-124;Couinaud, C., (1957) Le Foie - Etudes Anatomiques et Chirurgicales, , Masson, Paris; 
Strunk, H., Stuckmann, G., Textor, J., Willinek, W., Limit</style></pub-location><pages><style face="normal" font="default" size="100%">1435 - 1446</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Surgical planning of liver tumor resections requires detailed three-dimensional (3D) understanding of the complex arrangement of vasculature, liver segments and tumors. Knowledge about location and sizes of liver segments is important for choosing an optimal surgical resection approach and predicting postoperative residual liver capacity. The aim of this work is to facilitate such surgical planning process by developing a robust method for portal vein tree segmentation. The work also investigates the impact of vessel segmentation on the approximation of liver segment volumes. For segment approximation, smaller portal vein branches are of importance. Small branches, however, are difficult to segment due to noise and partial volume effects. Our vessel segmentation is based on the original gray-values and on the result of a vessel enhancement filter. Validation of the developed portal vein segmentation method in computer generated phantoms shows that, compared to a conventional approach, more vessel branches can be segmented. Experiments with in vivo acquired liver CT data sets confirmed this result. The outcome of a Nearest Neighbor liver segment approximation method applied to phantom data demonstrates, that the proposed vessel segmentation approach translates into a more accurate segment partitioning.</style></abstract><notes><style face="normal" font="default" size="100%">ScopusID: 5644267870doi: 10.1117/12.535514</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Csongor Halmai</style></author><author><style face="normal" font="default" size="100%">Balázs Erdőhelyi</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Krisztián Ollé</style></author><author><style face="normal" font="default" size="100%">Franz Lindbichler</style></author><author><style face="normal" font="default" size="100%">Gerhard Friedrich</style></author><author><style face="normal" font="default" size="100%">Karl Kiesler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">3D cross section of the laryngotracheal tract. A new method for visualization and quantification of tracheal stenoses</style></title><secondary-title><style face="normal" font="default" size="100%">RADIOLOGE</style></secondary-title><short-title><style face="normal" font="default" size="100%">RADIOLOGE</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2003///</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">43</style></volume><pages><style face="normal" font="default" size="100%">1056 - 1068</style></pages><isbn><style face="normal" font="default" size="100%">0033-832X</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">PURPOSE: Demonstration of a technique for 3D assessment oftracheal stenoses, regarding site, length and degree, based on 
spiral computed tomography (S-CT). PATIENTS AND METHODS: S-CT 
scanning and automated segmentation of the laryngo-tracheal 
tract (LTT) was followed by the extraction of the LTT medial 
axis using a skeletonisation algorithm. Orthogonal to the medial 
axis the LTT 3D cross sectional profile was computed and 
presented as line charts, where degree and length were obtained. 
Values for both parameters were compared between 36 patients and 
18 normal controls separately. Accuracy and precision was 
derived from 17 phantom studies. RESULTS: Average degree and 
length of tracheal stenoses were found to be 60.5% and 4.32 cm 
in patients compared to minor caliber changes of 8.8% and 2.31 
cm in normal controls (p &lt;0.005). For the phantoms an excellent 
correlation between the true and computed 3D cross sectional 
profile was found (p &lt;0.005) and an accuracy for length and 
degree measurements of 2.14 mm and 2.53% respectively could be 
determined. The corresponding figures for the precision were 
found to be 0.92 mm and 2.56%. CONCLUSION: LTT 3D cross 
sectional profiles permit objective, accurate and precise 
assessment of LTT caliber changes. Minor LTT caliber changes can 
be observed even in normals and, in case of an otherwise normal 
S-CT study, can be regarded as artefacts.
</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><notes><style face="normal" font="default" size="100%">UT: 000188058500005ScopusID: 9144241258doi: 10.1007/s00117-003-0990-8</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Csongor Halmai</style></author><author><style face="normal" font="default" size="100%">Balázs Erdőhelyi</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Krisztián Ollé</style></author><author><style face="normal" font="default" size="100%">Franz Lindbichler</style></author><author><style face="normal" font="default" size="100%">Gerhard Friedrich</style></author><author><style face="normal" font="default" size="100%">Karl Kiesler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">3D cross section of the laryngotracheal tract. A new method for visualization and quantification of tracheal stenoses</style></title><secondary-title><style face="normal" font="default" size="100%">RADIOLOGE</style></secondary-title><short-title><style face="normal" font="default" size="100%">RADIOLOGE</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2003///</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">43</style></volume><pages><style face="normal" font="default" size="100%">1056 - 1068</style></pages><isbn><style face="normal" font="default" size="100%">0033-832X</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">PURPOSE: Demonstration of a technique for 3D assessment oftracheal stenoses, regarding site, length and degree, based on 
spiral computed tomography (S-CT). PATIENTS AND METHODS: S-CT 
scanning and automated segmentation of the laryngo-tracheal 
tract (LTT) was followed by the extraction of the LTT medial 
axis using a skeletonisation algorithm. Orthogonal to the medial 
axis the LTT 3D cross sectional profile was computed and 
presented as line charts, where degree and length were obtained. 
Values for both parameters were compared between 36 patients and 
18 normal controls separately. Accuracy and precision was 
derived from 17 phantom studies. RESULTS: Average degree and 
length of tracheal stenoses were found to be 60.5% and 4.32 cm 
in patients compared to minor caliber changes of 8.8% and 2.31 
cm in normal controls (p &lt;0.005). For the phantoms an excellent 
correlation between the true and computed 3D cross sectional 
profile was found (p &lt;0.005) and an accuracy for length and 
degree measurements of 2.14 mm and 2.53% respectively could be 
determined. The corresponding figures for the precision were 
found to be 0.92 mm and 2.56%. CONCLUSION: LTT 3D cross 
sectional profiles permit objective, accurate and precise 
assessment of LTT caliber changes. Minor LTT caliber changes can 
be observed even in normals and, in case of an otherwise normal 
S-CT study, can be regarded as artefacts.
</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><notes><style face="normal" font="default" size="100%">UT: 000188058500005ScopusID: 9144241258doi: 10.1007/s00117-003-0990-8</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">R J Bale</style></author><author><style face="normal" font="default" size="100%">W Birkfellner</style></author><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">H Staedele</style></author><author><style face="normal" font="default" size="100%">J Kettenbach</style></author><author><style face="normal" font="default" size="100%">W Recheis</style></author><author><style face="normal" font="default" size="100%">M Voegele</style></author><author><style face="normal" font="default" size="100%">R Sweeney</style></author><author><style face="normal" font="default" size="100%">P Kovács</style></author><author><style face="normal" font="default" size="100%">R Wegenkittl</style></author><author><style face="normal" font="default" size="100%">G Bodner</style></author><author><style face="normal" font="default" size="100%">W Jaschke</style></author><author><style face="normal" font="default" size="100%">D zur Nedden</style></author><author><style face="normal" font="default" size="100%">E Eisner</style></author><author><style face="normal" font="default" size="100%">G Kronreig</style></author><author><style face="normal" font="default" size="100%">M Furst</style></author><author><style face="normal" font="default" size="100%">R Hanel</style></author><author><style face="normal" font="default" size="100%">M Figl</style></author><author><style face="normal" font="default" size="100%">H Bergmann</style></author><author><style face="normal" font="default" size="100%">D Hanson</style></author><author><style face="normal" font="default" size="100%">László Ruskó</style></author><author><style face="normal" font="default" size="100%">Lajos Rodek</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">Anna Vilanova Bartroli</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">A L Jacob</style></author><author><style face="normal" font="default" size="100%">B Baumann</style></author><author><style face="normal" font="default" size="100%">Emese Balogh</style></author><author><style face="normal" font="default" size="100%">P Messmer</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Medical Image Processing, Surgical Planning, Image-Guided Therapy and Robotic Applications: Recent Developments for Radiology</style></title><secondary-title><style face="normal" font="default" size="100%">EUROPEAN RADIOLOGY</style></secondary-title><short-title><style face="normal" font="default" size="100%">EUR RADIOL</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002///</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">504</style></pages><isbn><style face="normal" font="default" size="100%">0938-7994</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1 Suppl</style></issue><notes><style face="normal" font="default" size="100%">doi: 10.1007/s00330-002-0004-7</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Csongor Halmai</style></author><author><style face="normal" font="default" size="100%">Balázs Erdőhelyi</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Krisztián Ollé</style></author><author><style face="normal" font="default" size="100%">Bernhard Geiger</style></author><author><style face="normal" font="default" size="100%">Franz Lindbichler</style></author><author><style face="normal" font="default" size="100%">Gerhard Friedrich</style></author><author><style face="normal" font="default" size="100%">Karl Kiesler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spiral-CT-based assessment of tracheal stenoses using 3-D-skeletonization</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE TRANSACTIONS ON MEDICAL IMAGING</style></secondary-title><short-title><style face="normal" font="default" size="100%">IEEE T MED IMAGING</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002///</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">263 - 273</style></pages><isbn><style face="normal" font="default" size="100%">0278-0062</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">PURPOSE: Demonstration of a technique for three-dimensional (3-D) assessment of tracheal-stenoses, regarding site, length and 
degree, based on spiral computed tomography (S-CT). PATIENTS AND 
METHODS: S-CT scanning and automated segmentation of the 
laryngo-tracheal tract (LTT) was followed by the extraction of 
the LTT medial axis using a skeletonization algorithm. 
Orthogonal to the medial axis the LTT 3-D cross-sectional 
profile was computed and presented as line charts, where degree 
and length was obtained. Values for both parameters were 
compared between 36 patients and 18 normal controls separately. 
Accuracy and precision was derived from 17 phantom studies. 
RESULTS: Average degree and length of tracheal stenoses was 
found to be 60.5% and 4.32 cm in patients compared with minor 
caliber changes of 8.8% and 2.31 cm in normal controls (p &lt;&lt; 
0.0001). For the phantoms an excellent correlation between the 
true and computed 3-D cross-sectional profile was found (p &lt;&lt; 
0.005) and an accuracy for length and degree measurements of 
2.14 mm and 2.53% respectively could be determined. The 
corresponding figures for the precision were found to be 0.92 mm 
and 2.56%. CONCLUSION: LTT 3-D cross-sectional profiles permit 
objective, accurate and precise assessment of LTT caliber 
changes. Minor LTT caliber changes can be observed even in 
normals and, in case of an otherwise normal S-CT study, can be 
regarded as artifacts.
</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><notes><style face="normal" font="default" size="100%">UT: 000175063900007ScopusID: 0036489382doi: 10.1109/42.996344</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Georg Werkgartner</style></author><author><style face="normal" font="default" size="100%">Emese Balogh</style></author><author><style face="normal" font="default" size="100%">Anna Vilanova Bartroli</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">László Ruskó</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Virtual dissection and automated polyp detection of the colon based on spiral CT - Techniques and preliminary experience on a cadaveric phantom</style></title><secondary-title><style face="normal" font="default" size="100%">EUROPEAN SURGERY - ACTA CHIRURGICA AUSTRIACA</style></secondary-title><short-title><style face="normal" font="default" size="100%">EUR SURG-ACA</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002///</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">143 - 149</style></pages><isbn><style face="normal" font="default" size="100%">1682-8631</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Background: CT colonography was found to be sensitive andspecific for detection of colonic polyps and colorectal cancer 
(CRC). Depending on the software used, CT colonography requires 
a certain amount of operator interaction, which limits it's 
widespread usage. The goal of this papers is to present two 
novel automated techniques for displaying CT colonography: 
virtual dissection and automated colonic polyp detection. 
Methods: Virtual dissection refers to a technique where the 
entire colon is virtually stretched and flattened thus 
simulating the view on the pathologist's table. Colonic folds 
show a 'global outward bulging of the contour', whereas colonic 
polyps exhibit the inverse ('local inward bulging'). This 
feature is used to map areas of 'local inward bulging' with 
colours on 3D reconstructions. A cadaveric phantom with 13 
artificially inserted polyps was used for validation of both 
techniques. Results: On virtual dissection all 13 inserted 
polyps could be identified. They appeared either as bumps or as 
local broadening of colonic folds. In addition, the automated 
colonic polyp detection algorithm was able to tag all polyps. 
Only 10 min of operator interaction were necessary for both 
techniques. Conclusions: Virtual dissection overcomes the 
shortcomings of CT colonography, and automated colonic polyp 
detection establishes a roadmap of the polyps.
</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><notes><style face="normal" font="default" size="100%">ScopusID: 0037000327doi: 10.1046/j.1563-2563.2002.02018.x</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Emese Balogh</style></author><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">Attila Kuba</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Attila Kuba</style></author><author><style face="normal" font="default" size="100%">Eörs Máté</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Virtual Dissection of the Colon</style></title><secondary-title><style face="normal" font="default" size="100%">Képfeldolgozók és Alakfelismerők III. Konfereciája</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">NJSZT-KÉPAF</style></publisher><pub-location><style face="normal" font="default" size="100%">Szeged</style></pub-location><pages><style face="normal" font="default" size="100%">109 - 117</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Emese Balogh</style></author><author><style face="normal" font="default" size="100%">Anna Vilanova Bartroli</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Sven Lončarić</style></author><author><style face="normal" font="default" size="100%">Marco Subasic</style></author><author><style face="normal" font="default" size="100%">Domagoj Kovacevic</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Davide Caramella</style></author><author><style face="normal" font="default" size="100%">Carlo Bartolozzi</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Virtual Dissection of the Colon</style></title><secondary-title><style face="normal" font="default" size="100%">3D Image Processing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">New York</style></pub-location><pages><style face="normal" font="default" size="100%">197 - 209</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">doi: 10.1007/978-3-642-59438-0_18</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Emese Balogh</style></author><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">Attila Kuba</style></author><author><style face="normal" font="default" size="100%">Georg Werkgartner</style></author><author><style face="normal" font="default" size="100%">Ekke Spuller</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Seong Ki Mun</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Virtual dissection of the colon: technique and first experiments with artificial and cadaveric phantoms</style></title><secondary-title><style face="normal" font="default" size="100%">Medical Imaging 2002: Visualization, Image-Guided Procedures, and Display</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">SPIE</style></publisher><pub-location><style face="normal" font="default" size="100%">Bellingham; Washington</style></pub-location><pages><style face="normal" font="default" size="100%">713 - 721</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Virtual dissection refers to a display technique for polypdetection, where the colon is digitally straightened and then 
flattened using multirow detector Computed Tomograph (CT) 
images. As compared to virtual colonoscopy where polyps may be 
hidden from view behind the folds, the unravelled colon is more 
suitable for polyp detection, because the entire inner surface 
of the colon is displayed in a single view. The method was 
tested both on artificial and cadaveric phantoms. All polyps 
could be recognized on both phantoms. This technique for virtual 
dissection requires only a minimum of operator interaction.
</style></abstract><notes><style face="normal" font="default" size="100%">ScopusID: 0036061143doi: 10.1117/12.466982</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Emese Balogh</style></author><author><style face="normal" font="default" size="100%">Attila Kuba</style></author><author><style face="normal" font="default" size="100%">Csongor Halmai</style></author><author><style face="normal" font="default" size="100%">Balázs Erdőhelyi</style></author><author><style face="normal" font="default" size="100%">Klaus Hausegger</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A sequential 3D thinning algorithm and its medical applications</style></title><secondary-title><style face="normal" font="default" size="100%">LECTURE NOTES IN COMPUTER SCIENCE</style></secondary-title><short-title><style face="normal" font="default" size="100%">LECT NOTES COMPUT SCI</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2001///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.springerlink.com/content/py49qu0e434n0n16</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">2082</style></volume><pages><style face="normal" font="default" size="100%">409 - 415</style></pages><isbn><style face="normal" font="default" size="100%">0302-9743</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">doi: 10.1007/3-540-45729-1_42</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Emese Balogh</style></author><author><style face="normal" font="default" size="100%">Anna Vilanova Bartroli</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Sven Lončarić</style></author><author><style face="normal" font="default" size="100%">Hrvoje Babic</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Virtual Dissection of the Colon Based on Helical CT Data - Can It Be Done?</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 2nd International Symposium on Image and Signal Processing and Analysis, ISPA 2001, Pula, Croatia</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2001///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">University of Zagreb</style></publisher><pub-location><style face="normal" font="default" size="100%">Zagreb</style></pub-location><pages><style face="normal" font="default" size="100%">224 - 229</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Colorectal cancer is the third most commonly diagnosed cancer;and colonic polyps are known precursors of that particular 
cancer. Virtual dissection refers to a display technique for 
polyp detection based on helical CT data, where the colon is 
dissected and flattened as on the pathologist's table. The 
approach and image processing as well as the early experience 
are described in this paper.
</style></abstract><notes><style face="normal" font="default" size="100%">doi: 10.1109/ISPA.2001.938632</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Csongor Halmai</style></author><author><style face="normal" font="default" size="100%">Balázs Erdőhelyi</style></author><author><style face="normal" font="default" size="100%">László Martonossy</style></author><author><style face="normal" font="default" size="100%">Attila Kuba</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Tamas Sziranyi</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">3D vékonyítás és alkalmazása vérerek és légutak átmérőjének meghatározására</style></title><secondary-title><style face="normal" font="default" size="100%">A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2000</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan 2000</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">NJSZT</style></publisher><pub-location><style face="normal" font="default" size="100%">Noszvaj</style></pub-location><pages><style face="normal" font="default" size="100%">95 - 100</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Csongor Halmai</style></author><author><style face="normal" font="default" size="100%">Balázs Erdőhelyi</style></author><author><style face="normal" font="default" size="100%">László Martonossy</style></author><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">Bernhard Geiger</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Walter Hruby</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">New advances for imaging of laryngotracheal stenosis by post processing of spiral-CT data</style></title><secondary-title><style face="normal" font="default" size="100%">Digital (R)Evolution in Radiology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2000///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin; Heidelberg; New York; London; Paris; Tokyo</style></pub-location><pages><style face="normal" font="default" size="100%">275 - 285</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kálmán Palágyi</style></author><author><style face="normal" font="default" size="100%">Erich Sorantin</style></author><author><style face="normal" font="default" size="100%">Csongor Halmai</style></author><author><style face="normal" font="default" size="100%">Attila Kuba</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">3D thinning and its applications to medical image processing</style></title><secondary-title><style face="normal" font="default" size="100%">TASK QUARTERLY</style></secondary-title><short-title><style face="normal" font="default" size="100%">TASK Q</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year><pub-dates><date><style  face="normal" font="default" size="100%">1999///</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">397 - 408</style></pages><isbn><style face="normal" font="default" size="100%">1428-6394</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">4</style></issue></record></records></xml>