Publications

2021

Helm E., Schwebach J., Pointner A., Lin A., Rothensteiner V., Keimel D. and Schuler A. (2021). In Proceedings of dHealth 2021 – Health Informatics Meets Digital Health.

Abstract

There is a lack of secure official communication channels for peer review and peer feedback on medical findings. Objectives: We aimed to utilize the existing Austrian eHealth infrastructure to enable review and feedback processes. Methods: We extended the IHE XDW workflow document to enable the exchange of text messages (i.e., comments on documents or images) over an XDS infrastructure. Results: The workflow enabled the exchange of comments on specific sections of CDA documents or radiological images and was verified in an XDS test environment. Conclusion: The presented solution is a proof of concept that could lead to the specification of a new IHE workflow definition.

Helm E., Krauss O., Lin A., Pointner A., Schuler A. and Küng J. (2021). Process Mining on FHIR – An Open Standards-Based Process Analytics Approach for Healthcare. In Process Mining Workshops.

Abstract

Process mining has become its own research discipline over the last years, providing ways to analyze business processes based on event logs. In healthcare, the characteristics of organizational and treatment processes, especially regarding heterogeneous data sources, make it hard to apply process mining techniques. This work presents an approach to utilize established standards for accessing the audit trails of healthcare information systems and provides automated mapping to an event log format suitable for process mining. It also presents a way to simulate healthcare processes and uses it to validate the approach.

Further information can be found here

Langdon W. and Krauss O. (2021). Genetic Improvement of Data for Maths Functions*. In Proceedings of the Genetic and Evolutionary Computation Conference Companion.

Abstract

Genetic Improvement (GI) can be used to give better quality software and to create new functionality.
We show that GI can evolve the PowerPC open source GNU C runtime library square root function into cube root, binary logarithm log2 and reciprocal square root.
The GI cbrt is competitive in run-time performance and our inverted square root x**-0.5 is far more accurate than the approximation used in the Quake video game.
We use CMA-ES to adapt constants in a Newton-Raphson table, originally from glibc’s sqrt, for other double precision mathematics functions.
Such automatically customised math libraries might be used for mobile or low resource, IoT, mote, smart dust, bespoke cyber-physical systems.
Evolutionary Computing (EC) can be used to not only adapt source code but also data, such as numerical constants, and could enable a new way to conduct software data maintenance.
This is an exciting opportunity for the GECCO and optimisation communities.

Further information can be found here

Pointner A., Praschl C., Krauss O., Schuler A., Helm E., and Zwettler G. (2021). Line Clustering and Contour Extraction in the Context of 2D Building Plans. In Proceedings of 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision.

Abstract

For the purpose of analyzing a building according to its accessibility or structural resilience, printed 2D floor plans are not sufficient because of the missing link to semantic information.
This paper tackles this issue and introduces a concept for clustering classified lines of a floor plan and for creating semantically enriched contour elements based on different image processing,
computer vision and machine learning algorithms. Based on a general line clustering approach, we introduce type specific methods for walls, windows, doors and stairs.
The resulting clusters are in turn used for a contour creation, which uses minimal rotated rectangles. Those rectangles are transformed to polygons that are refined using post processing steps.The approach is evaluated via positive testing using a pixel-based comparison of the process’s result. For this, automatically generated as well as real world building plans are used. The final evaluation shows, that the concept reaches a confidence of >90% for door, stair and windows and only around 10% for stairs with the run-time linearly scaling with the size of the input.

Fernandez-Llatas, C., Munoz-Gama, J., Martin, N., Johnson, O., Sepulveda, M., & Helm, E. (2021). Process Mining in Healthcare. In Interactive Process Mining in Healthcare (pp. 41-52). Springer, Cham.

Abstract

Since medical processes are hard to be designed by consensus of experts, the use of data available for creating medical processes is a recurrent idea in literature. Data-driven paradigms are named to be a feasible solution in this field that can support medical experts in their daily decisions. Behind this paradigm, there are frameworks specifically designed for dealing with process-oriented problems. This is the case of process mining.

Zwettler, G.; Praschl, C.; Baumgartner, D.; Zucali, T.; Turk, D.; Hanreich, M. and Schuler, A. (2021). Three-step Alignment Approach for Fitting a Normalized Mask of a Person Rotating in A-Pose or T-Pose Essential for 3D Reconstruction based on 2D Images and CGI Derived Reference Target Pose.In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications – Volume 5: VISAPP, ISBN 978-989-758-488-6, pages 281-292. DOI: 10.5220/0010194102810292

Abstract

The 3D silhouette reconstruction of a human body rotating in front of a monocular camera system is a very challenging task due to elastic deformation and positional mismatch from body motion. Nevertheless, knowledge of the 3D body shape is a key information for precise determination of one’s clothing sizes, e.g. for precise shopping to reduce the number of return shipments in online retail. In this paper a novel three step alignment process is presented, utilizing As-Rigid-As-Possible (ARAP) transformations to normalize the body joint skeleton derived from OpenPose with a CGI rendered reference model in A- or T-pose. With further distance-map accelerated registration steps, positional mismatches and inaccuracies from the OpenPose joint estimation are compensated thus allowing for 3D silhouette reconstruction of a moving and elastic object without the need for sophisticated statistical shape models. Tests on both, artificial and real-world data, generally proof the practicability of th is approach with all three alignment/registration steps essential and adequate for 3D silhouette reconstruction data normalization.

2020

Baumgartner D., Jordens I., Wilfing D., Krauss O., Zwettler G. (2020). Automatic Detection of Objects Blocking Elevator Doors using Computer Vision. In Proceedings of the 23rd International Congress on Vertical Transportation Technologies.

Abstract

In this paper we present a new approach applying computer vision methods to image data acquired with depth perception cameras to map the interior of the elevator, detect the position and the state of the door and to detect objects in the door area. The depth data is used to determine the elevator cabin as safety cube, i.e. the position of the door, layout of the elevator and so on, while color data further enhances the detection of new objects. The approach can detect the state of the elevator door as either opened or closed, while no object is blocking the view to the door, as well as successfully identify objects blocking an open door. This elevator monitoring proves to be relevant for determination of the elevator state, safety as well aspects of predictive maintenance.

Int. J. Environ. Res. Public Health (Details)
Helm E., Lin M. A., Baumgartner D., Lin C. A., Küng J.

Proceedings of the 8th International Workshop on Genetic Improvement (Details)
Krauss O., Mössenböck H., Affenzeller M.

GECCO ’20: Proceedings of the Genetic and Evolutionary Computation Conference Companion (Details)
Langdon W., Krauss O.

Genetic Programming. EuroGP 2020. Lecture Notes in Computer Science, vol 12101. Springer, Cham (Details)
Krauss O., Langdon W.B.

Gerald Zwettler, David Holmes and Werner Backfrieder. “Strategies for Training Deep Learning Models in Medical Domains with Small Reference Datasets”. WSCG ’20.

Abstract

With the continuous progress of Deep Learning (DL) powerful tools are now available for sophisticated segmentation tasks. Nevertheless, the generally very high demand for training data and precise reference segmentations in the medical domain often cannot be met when dealing with small and individual studies or acquisition protocols. As common strategies, reinforcement learning or transfer learning are applicable, but coherent with immense effort due to domain-specific adaptation. In this work, we evaluate the applicability of a U-grid cascade for training on a very small set of abdominal MRI datasets of the parenchyma and discuss strategies to compensate for the lack of training data. Although model accuracy is rather low when training on 13 MRI bands with achievable JI=89.41, the results are still good enough for annual post-processing using a graph-cut (GC) approach with moderate user interaction requirements. In this way, DL models are retrained as additional test data sets become available to subsequently improve classification accuracy. With only 2 additional GC post-processing datasets, the accuracy after model retraining is JI= 89.87. Furthermore, the applicability of Generative Adversarial Networks (GAN) in the medical field is evaluated, discussing to synthesize axial CT slices together with perfect ground truth reference segmentations. It is shown for abdominal CT slices of the parenchyma that in the absence of training data, synthesized slices that can be derived in arbitrary numbers can significantly improve the DL training process when only an insufficient amount of data is available. While training on 2,200 real-world images only leads to an accuracy of JI=88.75, enrichment with 2,200 additional images synthesized from a GAN trained on 5,000 datasets leads to an increase up to JI=92.02. Even when the DL model is trained exclusively on 4,400 computer-generated images, the classification accuracy on real-world data is remarkable with JI=90.81.

G. Zwettler, D. Holmes III, W. Backfrieder – Pre- and Post-processing Strategies for Generic Slice-wise Segmentation of Tomographic 3D datasets Utilizing U-Net Deep Learning Models Trained for Specific Diagnostic Domains – Proceedings of the VISAPP 2020, Valetta, Malta, 2020, pp. 66-78

Abstract

An automated and generally applicable method for segmentation is still in the focus of medical image processing research. For several years, artificial intelligence methods have shown promising results, especially with widely available scalable deep learning libraries. In this work, a five-layer hybrid U-network is developed for slice-wise segmentation of liver datasets. The training data is obtained from the Medical Segmentation Decathlon database, which contains 131 fully segmented volumes. A slice-based segmentation model is implemented using Deep Learning algorithms with adjustments for variable parenchyma shape along the stacking direction and similarities between adjacent slices. Both are transformed for coronal and sagittal views. The implementation is done on a GPU rack using TensorFlow and Keras. Standardized volume and surface metrics are used for a quantitative measure of segmentation accuracy. The results DSC=97.59, JI=95.29 and NSD=99.37 show correct segmentation comparable to 3D U-meshes and other state of the art U-meshes. The development of a 2D slice oriented segmentation we justified by the advantages of short training times and lower complexity and also massively reduces memory consumption. This work manifests the high potential of AI methods for general application in medicine. Segmentation as a fully or semi-automatic tool under the supervision of the expert user.

Baumgartner,D., Praschl,C., Zucali,T., Zwettler,G.: 1. Hybrid Approach for Orientation-Estimation of Rotating Humans in Video Frames Acquired by Stationary Monocular Camera

Abstract

Accurate human orientation estimation with respect to the POSE of a monocular camera system is a challenging task due to general aspects of camera calibration and the deformability of a moving human body. Therefore, novel deep learning approaches for precise object position determination in robotics are difficult to adapt for human body analysis. In this work, we present a hybrid approach for accurately estimating a human body relative to a camera system, significantly improving the results derived from poseNet by applying optical flow analysis in a frame-to-frame comparison. The human body, which rotates in the T-position in situ, is thereby center-aligned, with object tracking methods applied to compensate for translations of the body motion. After 2D skeletal extraction, optical flow is calculated for an ROI region aligned relative to the vertical skeletal junction representing the spine and compared frame by frame. To evaluate the suitability of clothing as a basis for good features, local pixel homogeneity is considered to constrain optical flow to heterogeneous regions with distinguishing features such as imprint patterns, buttons, or buckles in addition to local illumination change. Based on the mean optical flow with rough approximation of the axial body shape as an ellipse, accuracy between 0.1° and 2.0° is achieved for orientation estimation on a frame-to-frame comparison evaluated and validated on both CGI renderings and real videos of people wearing clothes with different features.

International Journal of Simulation and Process Modelling

C. Praschl, O. Krauss, G. Zwettler

Abstract

This research covers generic approaches to determine the outdoor position and orientation of an augmented reality device due to the lack of outdoor suitability of depth or ambient sensing based devices currently available in the market. Orientation is primarily determined using an Attitude Heading Reference System (AHRS) for rough estimation. Based on a connected/integrated video camera, accuracy is improved for minor changes in orientation by using registration to evaluate orientation differences between two video frames, compensating for gyroscope drift errors. Position determination is performed using GPS with a real-time kinematic beacon system with rover and base station to achieve improved accuracy. The results show that based on the sensor application, AR hardware considered for indoor use can be retrofitted to work properly outdoors, at long distances, and even in moving vehicles. This will facilitate the future implementation of applications in various fields.

Daniel Dorfmeister, and Oliver Krauss. 2020. “Integrating HeuristicLab with Compilers and Interpreters for Non-Functional Code Optimization.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion – GECCO ’20. Cancun, Mexico: ACM Press. (Details).

Emmanuel Helm, Anna M. Lin, David Baumgartner, Alvin C. Lin und Josef Küng. 2020. “Adopting Standard Clinical Descriptors for Process Mining Case Studies in Healthcare”.

Abstract

Process mining can provide greater insight into medical treatment processes and organizational processes in healthcare. A review of case studies in the literature identified several different common aspects for comparison, which include methods, algorithms or techniques, medical domains, and healthcare specialties. However, from a medical perspective, clinical terms are not used in a consistent manner and do not follow a standardized clinical coding scheme. In addition, the characteristics of event log data are not always described. In this paper, we identified 38 clinically relevant case studies on process mining in healthcare published between 2016 and 2018 that described the tools, algorithms, and techniques used, as well as details about event log data. We then mapped the clinical aspects of the patient encounter environment, clinical specialty, and medical diagnoses using the standard SNOMED CT and ICD-10 clinical coding schemes. The possible results of adopting a standard approach for describing event log data and classifying medical terminology using standard clinical coding schemes are discussed.

2019

IGSOFT Softw. Eng. Notes 44, 3 (July 2019) (Details)
William B. Langdon, Westley Weimer, Christopher Timperley, Oliver Krauss, Zhen Yu Ding, Yiwei Lyu, Nicolas Chausseau, Eric Schulte, Shin Hwei Tan, Kevin Leach, Yu Huang, and Gabin An

arXiv preprint arXiv:1907.03773

Process-Oriented Data Science for Healthcare (Details)
Emmanuel Helm, David Baumgartner, Anna M. Lin, Alvin Lin, Josef Küng

Proceedings of the 6th International Workshop on Genetic Improvement
Oliver Krauss, Hanspeter Mössenböck, Michael Affenzeller

ICT for Health Science Research
A. Lin, O. Krauss, E. Helm

Process Mining Conference 2019 – 1st International Conference on Process Mining, June 24-26, 2019, Aachen, Germany
Baumgartner D., Haghofer A., Limberger M., Helm E.

Information Systems and Neuroscience, p. 221 – 228, Springer Verlag
Baumgartner D., Fischer T. Riedl R., Dreiseitl S.

2018

Proc. 9th Intl. Conf. on Society and Information Technologies (ICSIT 2018), Orlando, Vereinigte Staaten von Amerika, 2018, pp. 126-131
Mayr, H.

Proceeding ISSTA ’18 Companion Proceedings for the ISSTA/ECOOP 2018 Workshops Pages 144-149 (Details)
Schuler, A. and Anderst-Kotsis G. – MANA

International journal of environmental research and public health (Details)
Rinner C., Helm E., Dunkl R., Kittler H., Rinderle-Ma S.

GECCO ’18: Proceedings of the Genetic and Evolutionary Computation Conference Companion (Details)
Krauss, O. Mössenböck, H. Affenzeller, M. – GCE

International Conference on Business Process Management (Details)
Rinner C., Helm E., Dunkl R., Kittler H., Rinderle-Ma S.

Proceedings of the 30th European Modeling and Simulation Symposium EMSS2018, Budapest, Ungarn, 2018
A. Pointner, O. Krauss, G. Freilinger, D. Strieder, G. Zwettler – GUIDE

Proceedings of the 30th European Modeling and Simulation Symposium EMSS2018, Budapest, Ungarn, 2018
C. Praschl, O. Krauss, G. Zwettler – Drive for Knowledge

International Journal of Privacy and Health Information Management (IJPHIM)
Traxler B., Helm E., Krauss O., Schuler A., Kueng J.

European Journal of Biomedical Informatics (Details)
Lackerbauer A., Lin A., Krauss O., Hearn J., Helm E.

Studies in health technology and informatics
Helm E., Schuler A., Mayr H.

2017

Proceedings of the International Workshop on Innovative Simulation for Health Care (IWISH), Barcelona, Spanien, 2017, pp. 26-31
W. Backfrieder, B. Kerschbaumer, G. Zwettler

Proceedings of the International Workshop on Innovative Simulation for Healthcare IWISH 2017, Barcelona, Spanien, 2017
W. Backfrieder, G. Zwettler, B. Kerschbaumer

Akkordeon InhaltaSPLASH / OOPSLA 2017 (Details)
O. Krauss

ITBAM 2017, 8th International Conference on Information Technology in Bio-and Medical Informatics, Lyon, France (Details)
González López De Murillas E., Helm E., Reijers HA., Küng J., Bursa M., Holzinger A., Elena Renda M., Khuri S.

6th International Workshop on Innovative Simulation for Health Care (IWISH 2017) (Details)
E. Helm, B. Franz, A. Schuler, O. Krauss, J. Küng

Studies in Health Technology and Informatics, 2017 – 236 (Details)
Krauss O, Holzer K, Schuler A, Egelkraut R, Franz B. – KIMBO

2016

Information Technology in Bio- and Medical Informatics, Porto, Portugal, 2016 (Details)
E. Helm, J. Küng

IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference, Xi’an, Xi’an, China, 2016 (Details)
D. Wilfing, O. Krauss, A. Schuler – ARISE

IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference, Xi’an, Xi’an, China, 2016 (Details)
O. Krauss, D. Wilfing, A. Schuler – ARISE

Information Technology in Bio- and Medical Informatics, Porto, Portugal, 2016 (Details)
O. Krauss, M. Angermaier, E. Helm – KIMBO

2015

International Journal of Electronics and Telecommunications, Vol. 61, No. 2, 2015, pp. 151-157
O. Krauss, B. Franz, A. Schuler

NIEREN-UND HOCHDRUCKKRANKHEITEN, Vol. 44, No. 10, 2015, pp. 9
S. Porta, G. Zwettler, W. Kurschl, C. Dinu, G. Juttla, K. Pichlkastner, H. Gell, B. Kaiser, K. Kisters

International Journal of Electronics and Telecommunications, Vol. 60, No. 6, 2015, pp. 1-8
G. Zwettler, W. Backfrieder

Proceedings of the 2015 I-WISH, The International Workshop on Innovative Simulation for Healthcare , Bergeggi, Italien, 2015, pp. 6
W. Backfrieder, G. Zwettler

Proceedings of the IEEE International conference on Computing and Communications Technologies (ICCCT’15), Chennai, Indien, 2015, pp. 1-7
G. Zwettler, W. Backfrieder

eHealth2015 – Health Informatics Meets eHealth, Wien, Österreich, 2015 (Details)
E. Helm, A. Schuler, O. Krauss, B. Franz

European Journal for Biomedical Informatics, Vol. 11, No. 2, 2015 (Details)
B. Franz, A. Schuler, O. Krauss

International Journal of Electronics and Telecommunications, Vol. 61, No. 2, 2015 (Details)
A. Schuler, B. Franz, O. Krauss

MIE, Digital Healthcare Empowering Europeans, Madrid, Spanien, 2015, pp. 40-44 (Details)
F. Paster, E. Helm

International Journal of Electronics and Telecommunications, Vol. 61, No. 2, 2015, pp. 137-142 (Details)
E. Helm, F. Paster

2014

Proceedings of the 3rd International Workshop on Innovative Simulation for Healthcare IWISH 2014, Bordeaux, Frankreich, 2014, pp. 26-35
G. Zwettler, W. Backfrieder

Proceedings of the 3rd International Workshop on Innovative Simulation for Healthcare IWISH 2014, Bordeaux, France, 2014, pp. 36-41
W. Backfrieder, G. Zwettler

California, USA, Vereinigte Staaten von Amerika, 2014, pp. 9
G. Zwettler, W. Backfrieder

Tagungsband des 8. Forschungsforum der österreichischen Fachhochschulen, Kufstein, Österreich, 2014, pp. 296-300
G. Zwettler, W. Backfrieder

Tagungsband des 8. Forschungsforum der österreichischen Fachhochschulen, Kufstein, Österreich, 2014, pp. 482-483
G. Zwettler, W. Backfrieder

Gesundheitswesen im Wandel – nationale und internationale Perspektiven (Editors: Erwin Gollner, Magdalena Thaller) – Leykam, 2014, pp. 30-35 (Details)
A. Schuler

2013

Cross-Cultural Conference 2013, Steyr, Österreich, 2013, pp. 253-263
M. Gaisch, C. Holzmann, W. Kurschl, H. Mayr, S. Selinger

LECTURE NOTES IN COMPUTER SCIENCE, Vol. 8112, No. 1, 2013, pp. 166-173 (Details)
G. Zwettler, W. Backfrieder

Proceedings of The International Workshop on Innovative Simulation for Healthcare IWISH 2013 , Athens, Greece, Griechenland, 2013, pp. 58-64
G. Zwettler, W. Backfrieder

Proceedings of The International Workshop on Innovative Simulation for Healthcare IWISH 2013 , Athens, Greece, Griechenland, 2013, pp. 28-33
W. Backfrieder, B. Kerschbaumer, G. Zwettler

Proceedings of the 8th International Conference on Computer Vision Theory and Applications, Barcelona, Spanien, 2013, pp. 104-108
G. Zwettler, W. Backfrieder

Computer Aided Systems Theory (Eurocast 2013), Las Palmas, Spanien, 2013, pp. 118-119
G. Zwettler, W. Backfrieder

Proceedings of the 10th International Conference on Information Technology: New Generations (ITNG 2013), Las Vegas, Nevada, USA, 2013 (Details)
A. Schuler, B. Franz

6. Deutscher AAL-Kongress, Berlin, Deutschland, 2013, pp. 1-7 (Details)
B. Franz, M. Buchmayr, A. Schuler, W. Kurschl

Database and Expert Systems Applications, Prague, Tschechische Republik, 2013, pp. 466-473 (Details)
B. Franz, A. Schuler, E. Helm

eHealth2013 – Von der Wissenschaft zur Anwendung und zurück. , Wien, Österreich, 2013, pp. 207-218 (Details)
E. Helm, A. Schuler, H. Mayr

2012

Proceedings of the 24th European Modeling and Simulation Symposium EMSS 2012, Vienna, Österreich, 2012, pp. 73-81
G. Zwettler, W. Backfrieder

Tagungsband FFH 2012, Graz, Österreich, 2012, pp. 185-189
G. Zwettler, S. Hinterholzer, P. Track, F. Waschaurek, E. Hagmann, R. Woschitz

MIE, Quality of Life through Quality of Information, Pisa, Italien, 2012 (Details)
M. Strasser, E. Helm, A. Schuler, M. Fuschlberger, B. Altendorfer

Proceedings of the 10th International Conference on Information Communication Technologies in Health, Samos, Greece, Griechenland, 2012, pp. 422-432 (Details)
M. Strasser, E. Helm, B. Franz, H. Mayr

eHealth2012 – Health Informatics meets eHealth – von der Wissenschaft zur Anwendung und zurück, Wien, Österreich, 2012, pp. 179-184 (Details)
M. Strasser, E. Helm, A. Schuler, B. Franz, H. Mayr, C. David

Proceedings IV Kongress 2012, Linz, Österreich, 2012
H. Mayr, B. Franz

2011

eHealth 2011, Wien, Österreich, 2011, pp. 209-214
F. Pfeifer, B. Franz, E. Helm, J. Altmann, B. Aichinger

Proccedings of 23rd IEEE European Modeling & Simulation Symposium EMSS 2011, Roma, Italien, 2011, pp. 195-200
B. Franz, H. Mayr

Proceedings of the 23rd European Modeling & Simulation Symposium, Rom, Italien, 2011, pp. 111-117
G. Zwettler, W. Backfrieder, R. Pichler

Proceedings of the 23rd European Modeling & Simulation Symposium, Rom, Italien, 2011, pp. 100-104
W. Backfrieder, G. Zwettler

Tagungsband FFH 2011 (5. Forschungsforum der österreichischen Fachhochschulen), Wien (Favoriten), Österreich, 2011, pp. 38-41
G. Zwettler, W. Backfrieder, R. Pichler

Proc. of the 3rd International ICST Conference on IT Revolutions , Cordoba, Spanien, 2011, pp. 20
G. Zwettler, S. Hinterholzer, P. Track, R. Woschitz, F. Waschaurek, E. Hagmann

Proceedings of International Conference on Computer Aided Systems Theory EUROCAST 2011, Las Palmas, Spanien, 2011, pp. 233-235
G. Zwettler, S. Hinterholzer, F. Waschaurek, R. Woschitz, E. Hagmann, P. Track

Proceedings of International Conference on Computer Aided Systems Theory EUROCAST 2011, Las Palmas, Spanien, 2011, pp. 363-365
G. Zwettler, W. Backfrieder, R. Pichler

Proceedings IADIS International Conference e-Health 2011 – EH 2011, Rom, Italien, 2011, pp. 4
B. Franz, H. Mayr

2010

ÖKZ Das österreichische Gesundheitswesen, Vol. 51, No. 7, 2010, pp. 9-11
B. Franz, M. Lehner, M. Mayr

ECOOP 2010 – 1st Workshop on Testing Object-Oriented Software Systems, Maribor, Slowenien, 2010, pp. 9-15
A. Strasser, H. Mayr, T. Naderhirn

22nd European Modeling and Simulation Symposium EMSS 2010, Fes, Marokko, 2010, pp. 49-58
G. Zwettler, S. Hinterholzer, E. Hagmann, R. Woschitz, P. Track, F. Waschaurek

Tagungsband des 4. Forschungsforum der österreichischen Fachhochschulen, Pinkafeld, Österreich, 2010, pp. 79-84
G. Zwettler, W. Backfrieder

Intelligente Objekte und Mobile Informationssysteme im Gesundheitswesen, Erlangen, Deutschland, 2010
B. Franz, H. Mayr, M. Mayr

Proceedings of 7th International Conference on Information Technology : New Generations, Las Vegas, Vereinigte Staaten von Amerika, 2010
B. Franz, H. Mayr, M. Mayr

2009

eHealth2009, Wien, Österreich, 2009, pp. 115-121
J. Altmann, B. FRANZ, D. Mörtenschlag, F. Pfeifer, M. Strasser, B. Aichinger, R. Koller

Proceedings of 21st European Modeling and Simulation Symposium EMSS 2009, Tenerife, Spanien, 2009, pp. 3
J. Altmann, F. Pfeifer, M. Strasser, B. Franz, H. Mayr

Proceedings of 21st European Modeling and Simulation Symposium EMSS 2009, Tenerife, Spanien, 2009, pp. 161-166
G. Zwettler, W. Backfrieder, R. Swoboda, F. Pfeifer

Proceedings of 21st European Modeling and Simulation Symposium EMSS 2009, Tenerife, Spanien, 2009, pp. 154-160
R. Swoboda, G. Zwettler, J. Scharinger, C. Steinwender, F. Leisch

Tagungsband des 3. Forschungsforums der österreichischen Fachhochschulen, Fachhochschule Kärnten, Villach, Österreich, 2009, pp. 6
G. Zwettler, W. Backfrieder, R. Swoboda, F. Pfeifer

Tagungsband des 3. Forschungsforums der österreichischen Fachhochschulen, Fachhochschule Kärnten, Villach, Österreich, 2009, pp. 2
G. Zwettler, W. Backfrieder

Master/Diploma Thesis, FH OÖ Fakultät Hagenberg, Österreich, 2009, pp. 104
G. Zwettler

Proceedings of 21st European Modeling and Simulation Symposium EMSS 2009, Tenerife, Spanien, 2009, pp. 8
B. Franz, H. Mayr, M. Mayr, F. Pfeifer, J. Altmann, M. Lehner

Proceedings of the 6th International Conference on Information Technology : New Generations, Las Vegas, Vereinigte Staaten von Amerika, 2009
B. Franz, M. Lehner, H. Mayr, M. Mayr

Proceedings Med-e-Tel 2009, Global Telemedicine and eHealth Updates: Knowledge Resources Vol. 2, Luxembourg, Luxemburg, 2009, pp. 452-455
H. Mayr, B. Franz

2008

The Insight Journal, Vol. 3, No. 2, 2008, pp. 36
R. Swoboda, W. Backfrieder, G. Zwettler, F. Pfeifer

IGRT Vienna 2008 , Wien, Österreich, 2008, pp. 14
W. Backfrieder, G. Zwettler, R. Swoboda, F. Pfeifer, H. Kratochwill, F. Fellner

Challenges in Biosciences: Image Analysis and Pattern Recognition Aspects, St. Magdalena, Linz, Austria, Österreich, 2008, pp. 91-102
G. Zwettler, W. Backfrieder, F. Pfeifer, R. Swoboda

Proceedings of FFH2008 Fachhochschul Forschungs Forum, Wels, Österreich, 2008, pp. 253-259
G. Zwettler, W. Backfrieder, F. Pfeifer, R. Swoboda, H. Kratochwill, F. Fellner

Proceedings 2009 Tagungsband Bericht 2008 Journal Tagungsband – 6 – of FFH2008 Fachhochschul Forschungs Forum, Wels, Österreich, 2008, pp. 2
F. Pfeifer, W. Backfrieder, G. Zwettler, R. Swoboda, H. Kratochwill, M. Malek, R. Hainisch

Proceedings of the 3rd International Conference on Computer Vision Theory and Applications, Funchal, Madeira – Portugal, Portugal, 2008, pp. 74-80
G. Zwettler, W. Backfrieder, F. Pfeifer, R. Swoboda

Proceedings of the 20th European Modeling and Simulation Symposium, Campora S. Giovanni, Italien, 2008
C. Novak, B. Franz, H. Mayr, M. Vesely

Proceedings of The 2008 Internationa Conference on Machine Learning; Models, Technologies and Applications, Las Vegas, Vereinigte Staaten von Amerika, 2008, pp. 787-793
M. Vesely, C. Novak, A. Reh, H. Mayr

Proc. 23. STEV-Österreich-Fachtagung IT-/Software-Qualitätsmanagement in der Praxis, Wien, Österreich, 2008, pp. 48-59
H. Mayr

Proceedings of FFH2008 Fachhochschul Forschungs Forum, Wels, Österreich, 2008, pp. 3
J. Altmann, H. Mayr, W. Steinbichl

2007

Proceedings of International Mediterranean Modelling Multiconference I3M2007, Genoa, Italien, 2007, pp. 289-293
H. Mayr

Tagungsband des ersten Forschungsforum der österreichischen Fachhochschulen, Fachhochschule Salzburg, Campus Urstein, Österreich, 2007, pp. 244-250
H. Mayr, M. Vesely

Proc. 14th IEEE International Conference and Workshop on the Engineering of Computer Based Systems (ECBS’ 07), Tucson, Vereinigte Staaten von Amerika, 2007, pp. 397-402
H. Mayr

Proceedings of International Conference Computer Aided Systems Theory EUROCAST 2007, Las Palmas, Spanien, 2007, pp. 1097-1104
M. Vesely, H. Mayr

International Journal of Computer Assisted Radiology and Surgery, Berlin, Deutschland, 2007, pp. 460-461
W. Backfrieder, G. Zwettler, R. Swoboda, F. Pfeifer, H. Kratochwill, F. Fellner

Tagungsband des ersten Forschungsforum der österreichischen Fachhochschulen, Fachhochschule Salzburg, Campus Urstein, Österreich, 2007, pp. 425-426
G. Zwettler, W. Backfrieder, R. Swoboda, F. Pfeifer, H. Kratochwill, F. Fellner

Tagungsband des ersten Forschungsforum der österreichischen Fachhochschulen, Fachhochschule Salzburg, Campus Urstein, Österreich, 2007, pp. 401-402
F. Pfeifer, W. Backfrieder, R. Swoboda, G. Zwettler, H. Kratochwill, F. Fellner, M. Malek, R. Hainisch

2006

Proceedings FH Science Day 2006, Hagenberg, Österreich, 2006, pp. 74-80
F. Pfeifer, W. Backfrieder, R. Swoboda, G. Zwettler

Proceedings of the International Mediterranean Modelling Multiconference (I3M 2015), Barcelona, Spanien, 2006, pp. 675-680
G. Zwettler, R. Swoboda, W. Backfrieder, C. Steinwender, F. Leisch, C. Gabriel

2005

Proceedings of Conceptual Modeling and Simulation Conference (CMS 2005), Marseille, Frankreich, 2005, pp. 185-191
R. Swoboda, W. Backfrieder, G. Zwettler, M. Carpella, C. Steinwender, F. Leisch, C. Gabriel

Master/Diploma Thesis, FH OÖ Fakultät Hagenberg, Österreich, 2005, pp. 94
G. Zwettler