Kowarsch, F., Maurer-Granofszky, M., Weijler, L., Wödlinger, M., Reiter, M., Schumich, A., Feuerstein, T., Sala, S., Nováková, M., Faggin, G., Gaipa, G., Hrusak, O., Buldini, B., & Dworzak, M. (2023). FCM marker importance for MRD assessment in T-cell acute lymphoblastic leukemia: An AIEOP-BFM-ALL-FLOW study group report. Cytometry Part A. https://doi.org/10.1002/cyto.a.24805 ( reposiTUm)

Weijler, L., Kowarsch, F., Wödlinger, M., Reiter, M., Maurer-Granofszky, M., Schumich, A., & Dworzak, M. N. (2022). UMAP Based Anomaly Detection for Minimal Residual Disease Quantification within Acute Myeloid Leukemia. Cancers, 14(4), Article 898. https://doi.org/10.3390/cancers14040898 ( reposiTUm)

Wödlinger, M., Reiter, M., Weijler, L., Maurer-Granofszky, M., Schumich, A., Sajaroff, E., Groeneveld-Krentz, S., Rossi Jorge, Karawajew, L., Ratei, R., & Dworzak, M. (2022). Automated identification of cell populations in flow cytometry data with transformers. Computers in Biology and Medicine, 144, Article 105314. https://doi.org/10.1016/j.compbiomed.2022.105314 ( reposiTUm)

Reiter, M., Diem, M., Schumich, A., Maurer-Granofszky, M., Karawajew, L., Rossi, J. G., Ratei, R., Groenefeld-Krentz, S., Sajaroff, E., Suhendra, S., Kampel, M., & Dworzak, M. (2019). Automated Flow Cytometric MRD Assessment in Childhood Acute B‐ Lymphoblastic Leukemia Using Supervised Machine Learning. Cytometry Part A, 95(9), 966–975. https://doi.org/10.1002/cyto.a.23852 ( reposiTUm)

Groeneveld-Krentz, S., Schröder, M., Reiter, M., Pogodzinski, M., Pimentel-Gutiérrez, H., Vagkopoulou, R., Hof, J., Chen-Santel, C., Nebral, K., Bradtke, J., Türkmen, S., Baldus, C., Gattenlöhner, S., Haas, O., von Stackelberg, A., Karawajew, L., Eckert, C., & Kirschner-Schwabe, R. (2019). Aneuploidy in children with relapsed B-cell precursor acute lymphoblastic leukaemia: clinical importance of detecting a hypodiploid origin of relapse. British Journal of Haematology, 185(2), 266–283. https://doi.org/10.1111/bjh.15770 ( reposiTUm)

Reiter, M., Rota, P., Kleber, F., Diem, M., Groenefeld-Krentz, S., & Dworzak, M. (2016). Clustering of cell populations in flow cytometry data using a combination of Gaussian mixtures. Pattern Recognition, 60, 1029–1040. https://doi.org/10.1016/j.patcog.2016.04.004 ( reposiTUm)

Reiter, M., Hoffmann, J., Kleber, F., Schumich, A., Peter, G., Kromp, F., Kampel, M., & Dworzak, M. (2014). Towards automation of flow cytometric analysis for quality-assured follow-up assessment to guide curative therapy for acute lympholastic leukaemia in children. Magazine of European Medical Oncology, 7(4), 219–226. https://doi.org/10.1007/s12254-014-0172-6 ( reposiTUm)

Amirkhanov, A., Heinzl, C., Reiter, M., & Gröller, E. (2010). Visual Optimality and Stability Analysis of 3DCT Scan Positions. IEEE Transactions on Visualization and Computer Graphics, 16(6), 1477–1486. https://doi.org/10.1109/tvcg.2010.214 ( reposiTUm)

Donner, R., Reiter, M., Langs, G., Peloschek, P. L., & Bischof, H. (2006). Fast Active Appearance Model Search Using Canonical Correlation Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(10), 1690–1694. http://hdl.handle.net/20.500.12708/173411 ( reposiTUm)

Weijler, L., Reiter, M., Hermosilla, P., Maurer-Granofszky, M., & Dworzak, M. (2025). On the Importance of Local and Global Feature Learning for Automated Measurable Residual Disease Detection in Flow Cytometry Data. In A. Antonacopoulos, S. Chaudhuri, R. Chellappa, Cl. Liu, S. Bhattacharya, & U. Pal (Eds.), Pattern Recognition (pp. 316–331). https://doi.org/10.1007/978-3-031-78198-8_21 ( reposiTUm)

Weijler, L., Kowarsch, F., Reiter, M., Hermosilla, P., Maurer-Granofszky, M., & Dworzak, M. (2024). FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data. In 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (pp. 7941–7949). https://doi.org/10.1109/WACV57701.2024.00777 ( reposiTUm)

Lygizou, E. M., Reiter, M., Maurer-Granofszky, M., Dworzak, M., & Grosu, R. (2024). Automated Immunophenotyping Assessment for Diagnosing Childhood Acute Leukemia using Set-Transformers. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, United States of America (the). IEEE. https://doi.org/10.1109/EMBC53108.2024.10781595 ( reposiTUm)

Kowarsch, F., Weijler, L., Wödlinger, M., Reiter, M., Maurer-Granofszky, M., Schumich, A., Sajaroff, E., Groeneveld-Krentz, S., Rossi, J., Karawajew, L., Ratei, R., & Dworzak, M. (2022). Towards Self-explainable Transformers for Cell Classification in Flow Cytometry Data. In Interpretability of Machine Intelligence in Medical Image Computing (pp. 22–32). https://doi.org/10.1007/978-3-031-17976-1_3 ( reposiTUm)

Weijler, L., Diem, M., Reiter, M., & Maurer-Granofszky, M. (2021). Detecting Rare Cell Populations in Flow Cytometry Data Using UMAP. In 2020 25th International Conference on Pattern Recognition (ICPR). The 25th International Conference on Pattern Recognition (ICPR 2020), Mailand, Italy. https://doi.org/10.1109/icpr48806.2021.9413180 ( reposiTUm)

Licandro, R., Miloserdov, K., Reiter, M., & Kampel, M. (2019). GMM Interpolation for Blood Cell Cluster Alignment in Childhood Leukaemia. In A. Pichler, P. M. Roth, R. Sablatnig, G. Stübl, & M. Vincze (Eds.), Proceedings of the ARW & OAGM Workshop 2019 (pp. 179–182). Verlag der Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-663-5-39 ( reposiTUm)

Licandro, R., Reiter, M., Diem, M., Dworzak, M., Schumich, A., & Kampel, M. (2018). Application of Machine Learning for Automatic MRD Assessment in Paediatric Acute Myeloid Leukaemia. In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods. 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM), Funchal, Portugal. ScitePress. https://doi.org/10.5220/0006595804010408 ( reposiTUm)

Licandro, R., Schlegl, T., Reiter, M., Diem, M., Dworzak, M., Schumich, A., Langs, G., & Kampel, M. (2018). WGAN Latent Space Embeddings for Blast Identification in Childhood Acute Myeloid Leukaemia. In 2018 24th International Conference on Pattern Recognition (ICPR). 24th International Conference on Pattern Recognition (ICPR) 2018, Peking, China. IEEE. https://doi.org/10.1109/icpr.2018.8546177 ( reposiTUm)

Scheithe, J., Licandro, R., Rota, P., Reiter, M., Diem, M., & Kampel, M. (2018). Monitoring Acute Lymphoblastic Leukaemia Therapy with Stacked Denoising Autoencoders. In Computer Aided Intervention and Diagnostics in Clinical and Medical Images. International Conference on Clinical and Medical Image Analysis (ICCMIA18), Tamilnadu, India. Springer. http://hdl.handle.net/20.500.12708/57569 ( reposiTUm)

Licandro, R., Rota, P., Reiter, M., & Kampel, M. (2016). Flow Cytometry based automatic MRD assessment in Acute Lymphoblastic Leukaemia: Longitudinal evaluation of time-specific cell population models. In 2016 14th International Workshop on Content-Based Multimedia Indexing (CBMI). 14th International Workshop on Content-based Multimedia Indexing, Bukarest, Rumänien, EU. IEEE. https://doi.org/10.1109/cbmi.2016.7500274 ( reposiTUm)

Rota, P., Kleber, F., Reiter, M., Groenefeld-Krentz, S., & Kampel, M. (2016). The Role of Machine Learning in Medical Data Analysis. A Case Study: Flow Cytometry. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP 2016), Rom, Italien, EU. https://doi.org/10.5220/0005675903030310 ( reposiTUm)

Rota, P., Groenefeld-Krentz, S., & Reiter, M. (2015). On Automated Flow Cytometric Analysis for MRD Estimation of Acute Lymphoblastic Leukaemia: A Comparison Among Different Approaches. In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine. IEEE International Conference on Bioinformatics and Biomedicine, Washington, USA, Non-EU. IEEE. http://hdl.handle.net/20.500.12708/56172 ( reposiTUm)

Reiter, M., Kleber, F., Hoffmann, J., & Dworzak, M. (2014). Automation of MRD Measurements in Flow Cytometry to Guide Curative Therapy for ALL in Children. In 4th Munich Biomarker Conference Abstracts (p. 53). http://hdl.handle.net/20.500.12708/55290 ( reposiTUm)

Kromp, F., Taschner-Mandl, S., Schwarz, M., Blaha, J., Ambros, P., & Reiter, M. (2014). Semi-Automated Segmentation of Neuroblastoma Nuclei Using the Gradient Energy Tensor: A User Driven Approach. In 7th International Conference on Machine Vision (ICMV). 7th International Conference on Machine Vision (ICMV), Mailand, Italien, EU. http://hdl.handle.net/20.500.12708/55764 ( reposiTUm)

Reiter, M., Donner, R., Langs, G., & Bischof, H. (2006). Predicting Near Infrared Face Texture from Color Face Images using Canonical Correlation Analysis. In Digital Imaging and Pattern Recognition (pp. 161–167). OCG Schriftenreihe. http://hdl.handle.net/20.500.12708/51584 ( reposiTUm)

Reiter, M., Donner, R., Langs, G., & Bischof, H. (2006). Estimation of Face Depth Maps from Color Textures using Canonical Correlation Analysis. In Proceedings of the Computer Vision Winter Workshop (pp. 17–21). http://hdl.handle.net/20.500.12708/51585 ( reposiTUm)

Reiter, M., Donner, R., Langs, G., & Bischof, H. (2006). 3D and Infrared Face Reconstruction from RGB data using Canonical Correlation Analysis. In The 18th International Conference on Pattern Recognition. IAPR ICPR 2006, Hong Kong, Non-EU. IEEE Conmputer Society. http://hdl.handle.net/20.500.12708/51586 ( reposiTUm)

Langs, G., Peloschek, P. L., Donner, R., Reiter, M., & Bischof, H. (2006). Active Feature Models. In The 18th International Conference on Pattern Recognition (pp. 417–420). IEEE Society. http://hdl.handle.net/20.500.12708/51558 ( reposiTUm)

Donner, R., Langs, G., Reiter, M., & Bischof, H. (2005). CCA-based Active Appearance Model Search. In A. Hanbury & H. Bischof (Eds.), Computer Vision Winter Workshop 2005 (pp. 73–82). Eigenverlag. http://hdl.handle.net/20.500.12708/51329 ( reposiTUm)

Kowarsch, F., Weijler, L. M., Wödlinger, M. G., Kleber, F., Maurer-Granofszky, M., Reiter, M., & Dworzak, M. (2023, February 15). Explainable Visualization Techniques for Transformers in Flow Cytometry Data [Conference Presentation]. 26th Computer Vision Winter Workshop (CVWW) 2023, Krems an der Donau, Austria. ( reposiTUm)

Diem, M., Kleber, F., Reiter, M., Maurer-Granofzsky, M., Schumich, A., & Dworzak, M. (2019). FlowMe - A Clinical Decision Support System for Minimal Residual Disease Quantification for Acute Lymphoblastic Leukemia. AlpenFlow 2019, Bad Ischl, Austria. http://hdl.handle.net/20.500.12708/86944 ( reposiTUm)

Diem, M., Reiter, M., Kleber, F., & Dworzak, M. (2019). Quantifying Minimal Residual Disease in Flow Cytometry Measurements of Acute Lymphoblastic Leukemia Patients Automatically. Deutsche Gesellschaft für Zytometrie - Annual Meeting, Berlin, Germany. http://hdl.handle.net/20.500.12708/86943 ( reposiTUm)

Reiter, M., Diem, M., Maurer-Granofsky, M., Schuhmich, A., & Dworzak, M. (2018). Automation of flow-cytometric therapy response assessment in paediatric acute leukaemia using machine learning. From Lab to Life" Childhood Cancer Research Initiatives Symposium celebrating the 30th anniversary of the CCRI, Wien, Austria. http://hdl.handle.net/20.500.12708/86785 ( reposiTUm)

Reiter, M. (2016). Assessment of Flow Cytometry Data Using a Combination of Gaussian Mixture Models. Workshop on the ICT Contribution to the Development of Clinical Applications, Wien, Austria. http://hdl.handle.net/20.500.12708/86429 ( reposiTUm)

Licandro, R., Rota, P., Reiter, M., Kleber, F., Diem, M., & Kampel, M. (2016). Automatic Detection of Leukaemic Cells in Flow Cytometric Data for Minimal Residual Disease Assessment. EuroScience Open forum (ESOF) - Marie Sklodowska-Curie Actions Satellite Event `Research and Society’, Manchester, Großbritannien, EU. http://hdl.handle.net/20.500.12708/86365 ( reposiTUm)

Licandro, R., Rota, P., Reiter, M., & Kampel, M. (2016). AutoFLOW: a novel heuristic method to automatically detect leukaemic cells in flow cytometric data. 3rd Austrian Biomarker Symposium 2016 on early diagnostics, Wien, Austria. http://hdl.handle.net/20.500.12708/86368 ( reposiTUm)

Reiter, M., Kleber, F., Kampel, M., & Dworzak, M. (2014). AutoFLOW - Automation of Flow Cytometric Analysis for Quality-Assured Follow-up Assessment to Guide Curative Therapy for Acute Lymphoblastic Leukaemia in Children. 2nd Austrian Biomarker Symposium Vienna, Wien, Austria. http://hdl.handle.net/20.500.12708/85910 ( reposiTUm)

Zessner-Spitzenberg, M., Schaar, H. P., Zoboli, O., Kreuzinger, N., Kittlaus, S., Muschalla, D., Neunteufel, B., Gruber, G., Reinstaller, S., Camhy, D., Sommer, R., Reiter, M., Cervero-Arago, S., Holzhammer, E., Farnleitner, A., Steinbacher, S., Mayer, R., Ertl, T., De Vito-Francesco, E., … Hohenblum, P. (2022). Zukünftige stoffliche und mikrobiologische Herausforderungen für die kommunale Siedlungswasserwirtschaft, SIWAWI – Endbericht. http://hdl.handle.net/20.500.12708/80506 ( reposiTUm)