03874nas a2200733   4500008004100000020001400041245008100055210006900136260027000205300001600475490000700491520149600498100002001994700002402014700002202038700002002060700001902080700002102099700001802120700002202138700002302160700001902183700002002202700001702222700001902239700002202258700002302280700001402303700002102317700002202338700002002360700002002380700002202400700002002422700002302442700002402465700002302489700002302512700001902535700001802554700001802572700001802590700001202608700001402620700002402634700002002658700002202678700002202700700002502722700002002747700002102767700002002788700002102808700002002829700002102849700002202870700002002892700001902912700002702931700002302958700002002981700001403001856012503015       2009                        eng d  a0278-006200aComparison and evaluation of methods for liver segmentation from CT datasets0 aComparison and evaluation of methods for liver segmentation from  aPrice, 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. KacAug 2009  a1251 - 12650 v283 a<p>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 "MICCAI 2007 Grand Challenge" 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.</p>1 aHeimann, Tobias1 aVan Ginneken, Brahm1 aStyner, Martin, A1 aArzhaeva, Yulia1 aAurich, Volker1 aBauer, Christian1 aBeck, Andreas1 aBecker, Christoph1 aBeichel, Reinhardt1 aBekes, György1 aBello, Fernando1 aBinnig, Gerd1 aBischof, Horst1 aBornik, Alexander1 aCashman, Peter, MM1 aChi, Ying1 aCórdova, Andres1 aDawant, Benoit, M1 aFidrich, Márta1 aFurst, Jacob, D1 aFurukawa, Daisuke1 aGrenacher, Lars1 aHornegger, Joachim1 aKainmüller, Dagmar1 aKitney, Richard, I1 aKobatake, Hidefumi1 aLamecker, Hans1 aLange, Thomas1 aLee, Jeongjin1 aLennon, Brian1 aLi, Rui1 aLi, Senhu1 aMeinzer, Hans-Peter1 aNémeth, Gábor1 aRaicu, Daniela, S1 aRau, Anne-Mareike1 aVan Rikxoort, Eva, M1 aRousson, Mikael1 aRuskó, László1 aSaddi, Kinda, A1 aSchmidt, Günter1 aSeghers, Dieter1 aShimizu, Akinobi1 aSlagmolen, Pieter1 aSorantin, Erich1 aSoza, Grzegorz1 aSusomboon, Ruchaneewan1 aWaite, Jonathan, M1 aWimmer, Andreas1 aWolf, Ivo  uhttps://home.inf.u-szeged.hu/en/publication/comparison-and-evaluation-of-methods-for-liver-segmentation-from-ct-datasets01905nas a2200229   4500008004100000245007400041210006900115260003400184300001400218520110100232100002001333700001801353700002901371700002301400700002801423700002301451700002001474700001901494700002201513700002201535856011801557       2008                        eng d00aTechniques of Virtual Dissection of the Colon Based on Spiral CT Data0 aTechniques of Virtual Dissection of the Colon Based on Spiral CT  aBerlinbSpringer-Verlagc2008  a257 - 2683 a<p>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).</p>1 aSorantin, Erich1 aBalogh, Emese1 aBartroli, Anna, Vilanova1 aPalágyi, Kálmán1 aNyúl, László, Gábor1 aLindbichler, Franz1 aRuppert, Andrea1 aNeri, Emanuele1 aCaramella, Davide1 aBartolozzi, Carlo  uhttps://home.inf.u-szeged.hu/en/publication/techniques-of-virtual-dissection-of-the-colon-based-on-spiral-ct-data00405nas a2200097   4500008004100000245009300041210006900134260004500203300001400248856004500262       2006                        eng d00aNew advances for imaging laryngo / trachealstenosis by post processing of spiral-CT data0 aNew advances for imaging laryngo trachealstenosis by post proces  aWien; New YorkbSpringer-Verlagc2006///  a297 - 308  uhttps://home.inf.u-szeged.hu/en/node/90903069nas a2200109   4500008004100000245012500041210006900166260004100235300001200276520262600288856004502914       2005                        eng d00aTechniques in 3D Assessment of Tracheal-Stenosis by the Mean of Spiral Computed Tomography (S-CT) and Their Applications0 aTechniques in 3D Assessment of TrachealStenosis by the Mean of S  aSingaporebWorld Scientificc2005///  a61 - 803 aEndotracheal 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.
  uhttps://home.inf.u-szeged.hu/en/node/90801958nas a2200109   4500008004100000245007500041210006900116260027500185300001600460520132700476856004501803       2004                        eng d00aLiver segment approximation in CT data for surgical resection planning0 aLiver segment approximation in CT data for surgical resection pl  aBellingham; 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., LimitbSPIEc2004///  a1435 - 14463 aSurgical 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.  uhttps://home.inf.u-szeged.hu/en/node/93001903nas a2200133   4500008004100000020001400041245012200055210006900177260001200246300001600258490000700274520144300281856004501724       2003                        eng d  a0033-832X00a3D cross section of the laryngotracheal tract. A new method for visualization and quantification of tracheal stenoses0 a3D cross section of the laryngotracheal tract A new method for v  c2003///  a1056 - 10680 v433 aPURPOSE: 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 <0.005). For the phantoms an excellent 
correlation between the true and computed 3D cross sectional 
profile was found (p <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.
  uhttps://home.inf.u-szeged.hu/en/node/89501903nas a2200133   4500008004100000020001400041245012200055210006900177260001200246300001600258490000700274520144300281856004501724       2003                        eng d  a0033-832X00a3D cross section of the laryngotracheal tract. A new method for visualization and quantification of tracheal stenoses0 a3D cross section of the laryngotracheal tract A new method for v  c2003///  a1056 - 10680 v433 aPURPOSE: 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 <0.005). For the phantoms an excellent 
correlation between the true and computed 3D cross sectional 
profile was found (p <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.
  uhttps://home.inf.u-szeged.hu/en/node/99800448nas a2200121   4500008004100000020001400041245013000055210006900185260001200254300000800266490000700274856004500281       2002                        eng d  a0938-799400aMedical Image Processing, Surgical Planning, Image-Guided Therapy and Robotic Applications: Recent Developments for Radiology0 aMedical Image Processing Surgical Planning ImageGuided Therapy a  c2002///  a5040 v12  uhttps://home.inf.u-szeged.hu/en/node/93801889nas a2200133   4500008004100000020001400041245007800055210006900133260001200202300001400214490000700228520147500235856004501710       2002                        eng d  a0278-006200aSpiral-CT-based assessment of tracheal stenoses using 3-D-skeletonization0 aSpiralCTbased assessment of tracheal stenoses using 3Dskeletoniz  c2002///  a263 - 2730 v213 aPURPOSE: 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 << 
0.0001). For the phantoms an excellent correlation between the 
true and computed 3-D cross-sectional profile was found (p << 
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.
  uhttps://home.inf.u-szeged.hu/en/node/89601905nas a2200133   4500008004100000020001400041245014800055210006900203260001200272300001400284490000700298520142100305856004501726       2002                        eng d  a1682-863100aVirtual dissection and automated polyp detection of the colon based on spiral CT - Techniques and preliminary experience on a cadaveric phantom0 aVirtual dissection and automated polyp detection of the colon ba  c2002///  a143 - 1490 v343 aBackground: 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.
  uhttps://home.inf.u-szeged.hu/en/node/90000304nas a2200097   4500008004100000245003600041210003600077260003400113300001400147856004500161       2002                        eng d00aVirtual Dissection of the Colon0 aVirtual Dissection of the Colon  aSzegedbNJSZT-KÉPAFc2002///  a109 - 117  uhttps://home.inf.u-szeged.hu/en/node/90100309nas a2200097   4500008004100000245003600041210003600077260003900113300001400152856004500166       2002                        eng d00aVirtual Dissection of the Colon0 aVirtual Dissection of the Colon  aNew YorkbSpringer-Verlagc2002///  a197 - 209  uhttps://home.inf.u-szeged.hu/en/node/89901064nas a2200109   4500008004100000245010800041210006900149260004200218300001400260520063500274856004500909       2002                        eng d00aVirtual dissection of the colon: technique and first experiments with artificial and cadaveric phantoms0 aVirtual dissection of the colon technique and first experiments   aBellingham; WashingtonbSPIEc2002///  a713 - 7213 aVirtual 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.
  uhttps://home.inf.u-szeged.hu/en/node/89700403nas a2200121   4500008004100000020001400041245006800055210006600123260001200189300001400201490000900215856005700224       2001                        eng d  a0302-974300aA sequential 3D thinning algorithm and its medical applications0 asequential 3D thinning algorithm and its medical applications  c2001///  a409 - 4150 v2082  uhttp://www.springerlink.com/content/py49qu0e434n0n1600809nas a2200109   4500008004100000245007900041210006900120260004200189300001400231520040900245856004500654       2001                        eng d00aVirtual Dissection of the Colon Based on Helical CT Data - Can It Be Done?0 aVirtual Dissection of the Colon Based on Helical CT Data Can It   aZagrebbUniversity of Zagrebc2001///  a224 - 2293 aColorectal 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.
  uhttps://home.inf.u-szeged.hu/en/node/89800402nas a2200097   4500008004100000245009500041210008100136260002900217300001300246856004500259       2000                        eng d00a3D vékonyítás és alkalmazása vérerek és légutak átmérőjének meghatározására0 a3D vékonyítás és alkalmazása vérerek és légutak átmérőjének megh  aNoszvajbNJSZTcJan 2000  a95 - 100  uhttps://home.inf.u-szeged.hu/en/node/96700442nas a2200097   4500008004100000245009400041210006900135260008100204300001400285856004500299       2000                        eng d00aNew advances for imaging of laryngotracheal stenosis by post processing of spiral-CT data0 aNew advances for imaging of laryngotracheal stenosis by post pro  aBerlin; Heidelberg; New York; London; Paris; TokyobSpringer-Verlagc2000///  a275 - 285  uhttps://home.inf.u-szeged.hu/en/node/96100384nas a2200121   4500008004100000020001400041245006500055210006500120260001200185300001400197490000600211856004500217       1999                        eng d  a1428-639400a3D thinning and its applications to medical image processing0 a3D thinning and its applications to medical image processing  c1999///  a397 - 4080 v3  uhttps://home.inf.u-szeged.hu/en/node/958