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Urschler Martin |
** = Publications listed in SCI/SSCI/Pubmed
2025
Full paper/article (Journal)
** Coreelman, H; De, Tobel, J; Widek, T; Urschler, M; Fieuws, S; Thevissen, PW; Verstraete, KL
Magnetic resonance imaging for multi-factorial age estimation using Bayes' rule: a validation study in two independent samples.
Int J Legal Med. 2025;
Doi: 10.1007/s00414-025-03499-x
Web of Science
PubMed
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** Koziński, M; Oner, D; Gwizdała, J; Beigelman-Aubry, C; Fua, P; Koutsokera, A; Casutt, A; Vraka, A; De, Palma, M; Aubert, JD; Bischof, H; von, Garnier, C; Rahi, SJ; Urschler, M; Mansouri, N
Harnessing deep learning to detect bronchiolitis obliterans syndrome from chest CT.
Commun Med (Lond). 2025; 5(1): 18
Doi: 10.1038/s43856-025-00732-x
[OPEN ACCESS]
Web of Science
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** Sirocchi, C; Urschler, M; Pfeifer, B
Feature graphs for interpretable unsupervised tree ensembles: centrality, interaction, and application in disease subtyping.
BioData Min. 2025; 18(1): 15
Doi: 10.1186/s13040-025-00430-3
[OPEN ACCESS]
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** Van, Santvliet, L; Zappon, E; Gsell, MAF; Thaler, F; Blondeel, M; Dymarkowski, S; Claessen, G; Willems, R; Urschler, M; Vandenberk, B; Plank, G; De, Vos, M
Integrating anatomy and electrophysiology in the healthy human heart: Insights from biventricular statistical shape analysis using universal coordinates.
Comput Biol Med. 2025; 192(Pt A):110230
Doi: 10.1016/j.compbiomed.2025.110230
PubMed
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Pre-print
** Zappon, E; Azzolin, L; Gsell, MAF; Thaler, F; Prassl, AJ; Arnold, R; Gillette, K; Kariman, M; Manninger-Wünscher, M; Scherr, D; Neic, A; Urschler, M; Augustin, CM; Vigmond, EJ; Plank, G
An efficient end-to-end computational framework for the generation of ECG calibrated volumetric models of human atrial electrophysiology.
ArXiv. 2025;
[OPEN ACCESS]
PubMed
2024
Full paper/article (Journal)
** Hadzic, A; Urschler, M; Press, JA; Riedl, R; Rugani, P; Štern, D; Kirnbauer, B
Evaluating a Periapical Lesion Detection CNN on a Clinically Representative CBCT Dataset-A Validation Study.
J Clin Med. 2023; 13(1):
Doi: 10.3390/jcm13010197
[OPEN ACCESS]
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** Joham, SJ; Hadzic, A; Urschler, M
Implicit Is Not Enough: Explicitly Enforcing Anatomical Priors inside Landmark Localization Models.
Bioengineering (Basel). 2024; 11(9):
Doi: 10.3390/bioengineering11090932
[OPEN ACCESS]
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** Li, J; Zhou, Z; Yang, J; Pepe, A; Gsaxner, C; Luijten, G; Qu, C; Zhang, T; Chen, X; Li, W; Wodzinski, M; Friedrich, P; Xie, K; Jin, Y; Ambigapathy, N; Nasca, E; Solak, N; Melito, GM; Vu, VD; Memon, AR; Schlachta, C; De, Ribaupierre, S; Patel, R; Eagleson, R; Chen, X; Mächler, H; Kirschke, JS; de, la, Rosa, E; Christ, PF; Li, HB; Ellis, DG; Aizenberg, MR; Gatidis, S; Küstner, T; Shusharina, N; Heller, N; Andrearczyk, V; Depeursinge, A; Hatt, M; Sekuboyina, A; Löffler, MT; Liebl, H; Dorent, R; Vercauteren, T; Shapey, J; Kujawa, A; Cornelissen, S; Langenhuizen, P; Ben-Hamadou, A; Rekik, A; Pujades, S; Boyer, E; Bolelli, F; Grana, C; Lumetti, L; Salehi, H; Ma, J; Zhang, Y; Gharleghi, R; Beier, S; Sowmya, A; Garza-Villarreal, EA; Balducci, T; Angeles-Valdez, D; Souza, R; Rittner, L; Frayne, R; Ji, Y; Ferrari, V; Chatterjee, S; Dubost, F; Schreiber, S; Mattern, H; Speck, O; Haehn, D; John, C; Nürnberger, A; Pedrosa, J; Ferreira, C; Aresta, G; Cunha, A; Campilho, A; Suter, Y; Garcia, J; Lalande, A; Vandenbossche, V; Van, Oevelen, A; Duquesne, K; Mekhzoum, H; Vandemeulebroucke, J; Audenaert, E; Krebs, C; van, Leeuwen, T; Vereecke, E; Heidemeyer, H; Röhrig, R; Hölzle, F; Badeli, V; Krieger, K; Gunzer, M; Chen, J; van, Meegdenburg, T; Dada, A; Balzer, M; Fragemann, J; Jonske, F; Rempe, M; Malorodov, S; Bahnsen, FH; Seibold, C; Jaus, A; Marinov, Z; Jaeger, PF; Stiefelhagen, R; Santos, AS; Lindo, M; Ferreira, A; Alves, V; Kamp, M; Abourayya, A; Nensa, F; Hörst, F; Brehmer, A; Heine, L; Hanusrichter, Y; Weßling, M; Dudda, M; Podleska, LE; Fink, MA; Keyl, J; Tserpes, K; Kim, MS; Elhabian, S; Lamecker, H; Zukić, D; Paniagua, B; Wachinger, C; Urschler, M; Duong, L; Wasserthal, J; Hoyer, PF; Basu, O; Maal, T; Witjes, MJH; Schiele, G; Chang, TC; Ahmadi, SA; Luo, P; Menze, B; Reyes, M; Deserno, TM; Davatzikos, C; Puladi, B; Fua, P; Yuille, AL; Kleesiek, J; Egger, J
MedShapeNet - a large-scale dataset of 3D medical shapes for computer vision.
Biomed Tech (Berl). 2025; 70(1):71-90
Doi: 10.1515/bmt-2024-0396
Web of Science
PubMed
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** Pfeifer, B; Sirocchi, C; Bloice, MD; Kreuzthaler, M; Urschler, M
Federated unsupervised random forest for privacy-preserving patient stratification.
Bioinformatics. 2024; 40(Supplement_2): ii198-ii207.
Doi: 10.1093/bioinformatics/btae382
[OPEN ACCESS]
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** Sackl, M; Tinauer, C; Urschler, M; Enzinger, C; Stollberger, R; Ropele, S
Fully Automated Hippocampus Segmentation using T2-informed Deep Convolutional Neural Networks.
Neuroimage. 2024; 298: 120767
Doi: 10.1016/j.neuroimage.2024.120767
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** Stoleriu, MG; Pienn, M; Joerres, RA; Alter, P; Fero, T; Urschler, M; Kovacs, G; Olschewski, H; Kauczor, HU; Wielpütz, M; Jobst, B; Welte, T; Behr, J; Trudzinski, FC; Bals, R; Watz, H; Vogelmeier, CF; Biederer, J; Kahnert, K, , COSYCONET, Study, Group
Expiratory Venous Volume and Arterial Tortuosity are Associated with Disease Severity and Mortality Risk in Patients with COPD: Results from COSYCONET.
INT J CHRONIC OBSTR. 2024; 19: 1515-1529.
Doi: 10.2147/COPD.S458905
[OPEN ACCESS]
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Correction
** Rogers, M; Blanc-Talon, J; Urschler, M; Delmas, P
Wavelength and texture feature selection for hyperspectral imaging: a systematic literature review (vol 17, pg 6039, 2023)
J FOOD MEAS CHARACT. 2024; 18(1): 56-56.
Doi: 10.1007/s11694-023-02148-4
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2023
Review
** Rogers, M; Blanc-Talon, J; Urschler, M; Delmas, P
Wavelength and texture feature selection for hyperspectral imaging: a systematic literature review
J FOOD MEAS CHARACT. 2023;
Doi: 10.1007/s11694-023-02044-x
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2022
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** Bayat, A; Pace, DF; Sekuboyina, A; Payer, C; Stern, D; Urschler, M; Kirschke, JS; Menze, BH
Anatomy-Aware Inference of the 3D Standing Spine Posture from 2D Radiographs.
Tomography. 2022; 8(1): 479-496.
Doi: 10.3390/tomography8010039
[OPEN ACCESS]
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** Feng, S; Liu, Q; Patel, A; Bazai, SU; Jin, CK; Kim, JS; Sarrafzadeh, M; Azzollini, D; Yeoh, J; Kim, E; Gordon, S; Jang-Jaccard, J; Urschler, M; Barnard, S; Fong, A; Simmers, C; Tarr, GP; Wilson, B
Automated pneumothorax triaging in chest X-rays in the New Zealand population using deep-learning algorithms.
J Med Imaging Radiat Oncol. 2022; 66(8): 1035-1043.
Doi: 10.1111/1754-9485.13393
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2021
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** Feng, S; Azzollini, D; Kim, JS; Jin, CK; Gordon, SP; Yeoh, J; Kim, E; Han, M; Lee, A; Patel, A; Wu, J; Urschler, M; Fong, A; Simmers, C; Tarr, GP; Barnard, S; Wilson, B
Curation of the CANDID-PTX Dataset with Free-Text Reports.
Radiol Artif Intell. 2021; 3(6): e210136
Doi: 10.1148/ryai.2021210136
[OPEN ACCESS]
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** Gillette, K; Gsell, MAF; Prassl, AJ; Karabelas, E; Reiter, U; Reiter, G; Grandits, T; Payer, C; Štern, D; Urschler, M; Bayer, JD; Augustin, CM; Neic, A; Pock, T; Vigmond, EJ; Plank, G
A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs.
Med Image Anal. 2021; 71:102080
Doi: 10.1016/j.media.2021.102080
[OPEN ACCESS]
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** Sekuboyina, A; Husseini, ME; Bayat, A; Löffler, M; Liebl, H; Li, H; Tetteh, G; Kukačka, J; Payer, C; Štern, D; Urschler, M; Chen, M; Cheng, D; Lessmann, N; Hu, Y; Wang, T; Yang, D; Xu, D; Ambellan, F; Amiranashvili, T; Ehlke, M; Lamecker, H; Lehnert, S; Lirio, M; Olaguer, NP; Ramm, H; Sahu, M; Tack, A; Zachow, S; Jiang, T; Ma, X; Angerman, C; Wang, X; Brown, K; Kirszenberg, A; Puybareau, É; Chen, D; Bai, Y; Rapazzo, BH; Yeah, T; Zhang, A; Xu, S; Hou, F; He, Z; Zeng, C; Xiangshang, Z; Liming, X; Netherton, TJ; Mumme, RP; Court, LE; Huang, Z; He, C; Wang, LW; Ling, SH; Huỳnh, LD; Boutry, N; Jakubicek, R; Chmelik, J; Mulay, S; Sivaprakasam, M; Paetzold, JC; Shit, S; Ezhov, I; Wiestler, B; Glocker, B; Valentinitsch, A; Rempfler, M; Menze, BH; Kirschke, JS
VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images.
MED IMAGE ANAL. 2021; 73: 102166
Doi: 10.1016/j.media.2021.102166
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** Widek, T; Genet, P; Ehammer, T; Schwark, T; Urschler, M; Scheurer, E
Bone age estimation with the Greulich-Pyle atlas using 3T MR images of hand and wrist.
Forensic Sci Int. 2021; 319:110654
Doi: 10.1016/j.forsciint.2020.110654
[OPEN ACCESS]
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2020
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** Neumayer, B; Lesch, A; Thaler, F; Widek, T; Tschauner, S; De Tobel, J; Ehammer, T; Kirnbauer, B; Boldt, J; van Wijk, M; Stollberger, R; Urschler, M
The four-minute approach revisited: accelerating MRI-based multi-factorial age estimation.
Int J Legal Med. 2020; 134(4):1475-1485
Doi: 10.1007/s00414-019-02231-w
[OPEN ACCESS]
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2019
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** Jacob, J; Pienn, M; Payer, C; Urschler, M; Kokosi, M; Devaraj, A; Wells, AU; Olschewski, H
Quantitative CT-derived vessel metrics in idiopathic pulmonary fibrosis: A structure-function study.
Respirology. 2019; 24(5): 445-452.
Doi: 10.1111/resp.13485
[OPEN ACCESS]
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** Payer, C; Štern, D; Bischof, H; Urschler, M
Integrating spatial configuration into heatmap regression based CNNs for landmark localization.
Med Image Anal. 2019; 54:207-219
Doi: 10.1016/j.media.2019.03.007
[OPEN ACCESS]
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** Payer, C; Štern, D; Feiner, M; Bischof, H; Urschler, M
Segmenting and tracking cell instances with cosine embeddings and recurrent hourglass networks.
Med Image Anal. 2019; 57:106-119
Doi: 10.1016/j.media.2019.06.015
[OPEN ACCESS]
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** Stern, D; Payer, C; Giuliani, N; Urschler, M
Automatic Age Estimation and Majority Age Classification From Multi-Factorial MRI Data.
IEEE J Biomed Health Inform. 2019; 23(4):1392-1403
Doi: 10.1109/JBHI.2018.2869606
[OPEN ACCESS]
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** Štern, D; Payer, C; Urschler, M
Automated age estimation from MRI volumes of the hand.
Med Image Anal. 2019; 58:101538
Doi: 10.1016/j.media.2019.101538
[OPEN ACCESS]
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** Zhuang, X; Li, L; Payer, C; Štern, D; Urschler, M; Heinrich, MP; Oster, J; Wang, C; Smedby, Ö; Bian, C; Yang, X; Heng, PA; Mortazi, A; Bagci, U; Yang, G; Sun, C; Galisot, G; Ramel, JY; Brouard, T; Tong, Q; Si, W; Liao, X; Zeng, G; Shi, Z; Zheng, G; Wang, C; MacGillivray, T; Newby, D; Rhode, K; Ourselin, S; Mohiaddin, R; Keegan, J; Firmin, D; Yang, G
Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge.
Med Image Anal. 2019; 58:101537
Doi: 10.1016/j.media.2019.101537
[OPEN ACCESS]
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Abstract (Journal)
** Jacob, J; Pienn, M; Payer, C; Urschler, M; Kokosi, M; Devaraj, A; Wells, AU; Olschewski, H
Normalized Vessel Volume from Quantitative Computed Tomography Predicts Survival in Idiopathic Pulmonary Fibrosis.
AM J RESP CRIT CARE. 2019; 199: -International Conference of the American-Thoracic-Society; MAY 17-22, 2019; Dallas, TX.
[Oral Communication]
Web of Science
2018
Full paper/article (Journal)
** Bornik, A; Urschler, M; Schmalstieg, D; Bischof, H; Krauskopf, A; Schwark, T; Scheurer, E; Yen, K
Integrated computer-aided forensic case analysis, presentation, and documentation based on multimodal 3D data.
Forensic Sci Int. 2018; 287:12-24
Doi: 10.1016/j.forsciint.2018.03.031
[OPEN ACCESS]
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** Neumayer, B; Schloegl, M; Payer, C; Widek, T; Tschauner, S; Ehammer, T; Stollberger, R; Urschler, M
Reducing acquisition time for MRI-based forensic age estimation.
Sci Rep. 2018; 8(1): 2063-2063.
Doi: 10.1038/s41598-018-20475-1
[OPEN ACCESS]
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** Pienn, M; Burgard, C; Payer, C; Avian, A; Urschler, M; Stollberger, R; Olschewski, A; Olschewski, H; Johnson, T; Meinel, FG; Bálint, Z
Healthy Lung Vessel Morphology Derived From Thoracic Computed Tomography.
Front Physiol. 2018; 9(1):346-346
Doi: 10.3389/fphys.2018.00346
[OPEN ACCESS]
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** Urschler, M; Ebner, T; Štern, D
Integrating geometric configuration and appearance information into a unified framework for anatomical landmark localization.
Med Image Anal. 2018; 43:23-36
Doi: 10.1016/j.media.2017.09.003
[OPEN ACCESS]
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2017
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** Kainz, P; Pfeiffer, M; Urschler, M
Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization.
PeerJ. 2017; 5(6):e3874-e3874
Doi: 10.7717/peerj.3874
[OPEN ACCESS]
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** Martínez Vera, NP; Höller, J; Widek, T; Neumayer, B; Ehammer, T; Urschler, M
Forensic age estimation by morphometric analysis of the manubrium from 3D MR images.
Forensic Sci Int. 2017; 277(7):21-29
Doi: 10.1016/j.forsciint.2017.05.005
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** Ogris, K; Petrovic, A; Scheicher, S; Sprenger, H; Urschler, M; Hassler, EM; Yen, K; Scheurer, E
Detection and volume estimation of artificial hematomas in the subcutaneous fatty tissue: comparison of different MR sequences at 3.0 T.
Forensic Sci Med Pathol. 2017; 13(2):135-144
Doi: 10.1007/s12024-017-9847-8
[OPEN ACCESS]
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** Zheng, G; Chu, C; Belavý, DL; Ibragimov, B; Korez, R; Vrtovec, T; Hutt, H; Everson, R; Meakin, J; Andrade, IL; Glocker, B; Chen, H; Dou, Q; Heng, PA; Wang, C; Forsberg, D; Neubert, A; Fripp, J; Urschler, M; Stern, D; Wimmer, M; Novikov, AA; Cheng, H; Armbrecht, G; Felsenberg, D; Li, S
Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: A grand challenge.
Med Image Anal. 2017; 35:327-344
Doi: 10.1016/j.media.2016.08.005
[OPEN ACCESS]
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Review
** Sirinukunwattana, K; Pluim, JPW; Chen, H; Qi, X; Heng, PA; Guo, YB; Wang, LY; Matuszewski, BJ; Bruni, E; Sanchez, U; Böhm, A; Ronneberger, O; Cheikh, BB; Racoceanu, D; Kainz, P; Pfeiffer, M; Urschler, M; Snead, DRJ; Rajpoot, NM
Gland segmentation in colon histology images: The glas challenge contest.
Med Image Anal. 2017; 35(3):489-502
Doi: 10.1016/j.media.2016.08.008
[OPEN ACCESS]
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Abstract (Journal)
** Giuliani, N; Urschler, M; Olschewski, A; Olschewski, H; Pienn, M
Fully-automatic lung fissure detection from thoracic computed tomography images
WIEN KLIN WOCHENSCHR. 2017; 129(19-20):767-767.-41. Jahrestagung der Österreichischen Gesellschaft für Pneumologie und 1. Jahrestagung der Österreichischen Gesellschaft für Thoraxchirurgie; OCT 5–7, 2017; Innsbruck, AUSTRIA.
[Poster]
Web of Science
** Pienn, M; Burgard, C; Payer, C; Urschler, M; Johnson, T; Stollberger, R; Olschewski, A; Olschewski, H; Meinel, FG; Balint, Z
Age-related changes in lung vessel morphology in healthy men and women
WIEN KLIN WOCHENSCHR. 2017; 129(19-20):756-756.-41. Jahrestagung der Österreichischen Gesellschaft für Pneumologie und 1. Jahrestagung der Österreichischen Gesellschaft für Thoraxchirurgie; OCT 5–7, 2017; Innsbruck, AUSTRIA.
[Poster]
Web of Science
2016
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** Payer, C; Pienn, M; Bálint, Z; Shekhovtsov, A; Talakic, E; Nagy, E; Olschewski, A; Olschewski, H; Urschler, M
Automated integer programming based separation of arteries and veins from thoracic CT images.
Med Image Anal. 2016; 34:109-122
Doi: 10.1016/j.media.2016.05.002
[OPEN ACCESS]
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** Urschler, M; Krauskopf, A; Widek, T; Sorantin, E; Ehammer, T; Borkenstein, M; Yen, K; Scheurer, E
Applicability of Greulich-Pyle and Tanner-Whitehouse grading methods to MRI when assessing hand bone age in forensic age estimation: A pilot study.
Forensic Sci Int. 2016; 266(9):281-288
Doi: 10.1016/j.forsciint.2016.06.016
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** Wernitznig, S; Sele, M; Urschler, M; Zankel, A; Pölt, P; Rind, FC; Leitinger, G
Optimizing the 3D-reconstruction technique for serial block-face scanning electron microscopy.
J Neurosci Methods. 2016; 264(9):16-24
Doi: 10.1016/j.jneumeth.2016.02.019
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** Yao, J; Burns, JE; Forsberg, D; Seitel, A; Rasoulian, A; Abolmaesumi, P; Hammernik, K; Urschler, M; Ibragimov, B; Korez, R; Vrtovec, T; Castro-Mateos, I; Pozo, JM; Frangi, AF; Summers, RM; Li, S
A multi-center milestone study of clinical vertebral CT segmentation.
Comput Med Imaging Graph. 2016; 49(4):16-28
Doi: 10.1016/j.compmedimag.2015.12.006
[OPEN ACCESS]
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Abstract (Journal)
** Pienn, M; Payer, C; Urschler, M; Salvan-Schaschl, C; Neuwirth, R; Stollberger, R; Kovacs, G; Foris, V; Olschewski, A; Olschewski, H; Balint, Z
Reduced Venous Vessel Density In Pre-Capillary Pulmonary Hypertension
AM J RESP CRIT CARE. 2016; 193: -International Conference of the American-Thoracic-Society (ATS); MAY 13-18, 2016; San Francisco, CA.
[Poster]
Web of Science
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2015
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** Baumann, P; Widek, T; Merkens, H; Boldt, J; Petrovic, A; Urschler, M; Kirnbauer, B; Jakse, N; Scheurer, E
Dental age estimation of living persons: Comparison of MRI with OPG.
Forensic Sci Int. 2015; 253: 76-80.
Doi: 10.1016/j.forsciint.2015.06.001
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** Urschler, M; Grassegger, S; Štern, D
What automated age estimation of hand and wrist MRI data tells us about skeletal maturation in male adolescents.
Ann Hum Biol. 2015; 42(4):358-367
Doi: 10.3109/03014460.2015.1043945
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** Webb, BA; Petrovic, A; Urschler, M; Scheurer, E
Assessment of fiducial markers to enable the co-registration of photographs and MRI data.
Forensic Sci Int. 2015; 248(2):148-153
Doi: 10.1016/j.forsciint.2014.12.027
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Abstract (Journal)
** Payer, C; Pienn, M; Urschler, M; Kovacs, G; Douschan, P; Olschewski, A; Olschewski, H; Balint, Z
Regional differences in lung vessel morphology from thoracic CT images
WIEN KLIN WOCHENSCHR. 2015; 127(19-20):812-812.
[Oral Communication]
Web of Science
** Pienn, M; Payer, C; Kovacs, G; Foris, V; Urschler, M; Olschewski, A; Olschewski, H; Balint, Z
Pulmonary arterial tortuosity as a non-invasive diagnostic tool for pulmonary arterial hypertension
WIEN KLIN WOCHENSCHR. 2015; 127(19-20):822-822.
[Poster]
Web of Science
2014
Full paper/article (Journal)
** Ebner, T; Stern, D; Donner, R; Bischof, H; Urschler, M
Towards automatic bone age estimation from MRI: localization of 3D anatomical landmarks.
Med Image Comput Comput Assist Interv. 2014; 17(Pt 2):421-428
PubMed
** Helmberger, M; Pienn, M; Urschler, M; Kullnig, P; Stollberger, R; Kovacs, G; Olschewski, A; Olschewski, H; Bálint, Z
Quantification of tortuosity and fractal dimension of the lung vessels in pulmonary hypertension patients.
PLoS One. 2014; 9(1):e87515-e87515
Doi: 10.1371/journal.pone.0087515
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** Rudyanto, RD; Kerkstra, S; van Rikxoort, EM; Fetita, C; Brillet, PY; Lefevre, C; Xue, W; Zhu, X; Liang, J; Öksüz, I; Ünay, D; Kadipaşaoğlu, K; Estépar, RS; Ross, JC; Washko, GR; Prieto, JC; Hoyos, MH; Orkisz, M; Meine, H; Hüllebrand, M; Stöcker, C; Mir, FL; Naranjo, V; Villanueva, E; Staring, M; Xiao, C; Stoel, BC; Fabijanska, A; Smistad, E; Elster, AC; Lindseth, F; Foruzan, AH; Kiros, R; Popuri, K; Cobzas, D; Jimenez-Carretero, D; Santos, A; Ledesma-Carbayo, MJ; Helmberger, M; Urschler, M; Pienn, M; Bosboom, DG; Campo, A; Prokop, M; de Jong, PA; Ortiz-de-Solorzano, C; Muñoz-Barrutia, A; van Ginneken, B
Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study.
Med Image Anal. 2014; 18(7):1217-1232
Doi: 10.1016/j.media.2014.07.003
[OPEN ACCESS]
Web of Science
PubMed
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** Stern, D; Ebner, T; Bischof, H; Grassegger, S; Ehammer, T; Urschler, M
Fully automatic bone age estimation from left hand MR images.
Med Image Comput Comput Assist Interv. 2014; 17(Pt 2):220-227
PubMed
** Urschler, M; Höller, J; Bornik, A; Paul, T; Giretzlehner, M; Bischof, H; Yen, K; Scheurer, E
Intuitive presentation of clinical forensic data using anonymous and person-specific 3D reference manikins.
Forensic Sci Int. 2014; 241(16):155-166
Doi: 10.1016/j.forsciint.2014.05.017
Web of Science
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Abstract (Journal)
** Balint, Z; Pienn, M; Helmberger, M; Urschler, M; Kullnig, P; Stollberger, R; Kovacs, G; Olschewski, A; Olschewski, H
Comparison Of Quantitative Lung Vessel Tortuosity And Echocardiography For Non-Invasive Detection Of Pulmonary Hypertension.
AM J RESP CRIT CARE. 2014; 189: -ATS 2014; MAY 16-21, 2014; San Diego, California, USA.
[Poster]
Web of Science
** Pienn, M; Helmberger, M; Urschler, M; Kullnig, P; Stollberger, R; Kovacs, G; Olschewski, A; Olschewski, H; Balint, Z
Quantification Of Lung Vessel Tortuosity In Pulmonary Hypertension Patients.
AM J RESP CRIT CARE. 2014; 189: -ATS 2014; MAY 16-21, 2014; San Diego, California, USA.
[Oral Communication]
Web of Science
2013
Abstract (Journal)
** Bálint, Z; Helmberger, M; Pienn, M; Kovacs, G; Tscherner, M; Urschler, M; Olschewski, A; Olschewski, H;
Quantitative determination of lung vessel tortuosity, but not fractal dimension correlates with lung function parameters of PH patients.
WIEN KLIN WOCHENSCHR. 2013; 125(19-20):647-647.-Jahrestagung der Österreichischen Gesellschaft für Pneumologie; OKT 24-26, 2013; Vienna, AUSTRIA.
[Poster]
Web of Science
2012
Full paper/article (Journal)
** Urschler, M; Bornik, A; Scheurer, E; Yen, K; Bischof, H; Schmalstieg, D
Forensic-Case Analysis: From 3D Imaging to Interactive Visualization
IEEE COMPUT GRAPH. 2012; 32(4): 79-87.
Doi: 10.1109/MCG.2012.75
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** Urschler, M; Bornik, A; Scheurer, E; Yen, K; Bischof, H; Schmalstieg, D
Forensic-case analysis: from 3D imaging to interactive visualization.
IEEE Comput Graph Appl. 2012; 32(4): 79-87.
Doi: 10.1109/MCG.2012.75
PubMed
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2011
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** Murphy, K; van Ginneken, B; Reinhardt, JM; Kabus, S; Ding, K; Deng, X; Cao, K; Du, K; Christensen, GE; Garcia, V; Vercauteren, T; Ayache, N; Commowick, O; Malandain, G; Glocker, B; Paragios, N; Navab, N; Gorbunova, V; Sporring, J; de Bruijne, M; Han, X; Heinrich, MP; Schnabel, JA; Jenkinson, M; Lorenz, C; Modat, M; McClelland, JR; Ourselin, S; Muenzing, SE; Viergever, MA; De Nigris, D; Collins, DL; Arbel, T; Peroni, M; Li, R; Sharp, GC; Schmidt-Richberg, A; Ehrhardt, J; Werner, R; Smeets, D; Loeckx, D; Song, G; Tustison, N; Avants, B; Gee, JC; Staring, M; Klein, S; Stoel, BC; Urschler, M; Werlberger, M; Vandemeulebroucke, J; Rit, S; Sarrut, D; Pluim, JP
Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge.
IEEE Trans Med Imaging. 2011; 30(11):1901-1920
Doi: 10.1109/TMI.2011.2158349
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2007
Full paper/article (Journal)
** Pock, T; Urschler, M; Zach, C; Beichel, R; Bischof, H
A duality based algorithm for TV-L1-optical-flow image registration.
Med Image Comput Comput Assist Interv. 2007; 10(Pt 2): 511-518.
Doi: 10.1007/978-3-540-75759-7_62
PubMed
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2006
Full paper/article (Proceedings)
** Micu, R; Jakobs, TF; Urschler, M; Navab, N
A new registration/visualizat ion paradigm for CT-fluoroscopy guided RF liver ablation
LECT NOTES COMPUT SC. 2006; 4190: 882-890.
Doi: 10.1007/11866565_108
Web of Science
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** Urschler, M; Bauer, J; Ditt, H; Bischof, H
SIFT and shape context for feature-based nonlinear registration of thoracic CT images
LECT NOTES COMPUT SC. 2006; 4241: 73-84.
Doi: 10.1007/11889762_7
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** Urschler, M; Zach, C; Ditt, H; Bischof, H
Automatic point landmark matching for regularizing nonlinear intensity registration: Application to thoracic CT images
LECT NOTES COMPUT SC. 2006; 4191: 710-717.
Doi: 10.1007/11866763_87
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