@inproceedings{AubrevilleBertramKlopfleischetal.2019, author = {Aubreville, Marc and Bertram, Christof and Klopfleisch, Robert and Maier, Andreas}, title = {Field of Interest Proposal for Augmented Mitotic Cell Count}, volume = {2}, booktitle = {Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOIMAGING}, subtitle = {Comparison of Two Convolutional Networks}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-353-7}, issn = {2184-4305}, doi = {https://doi.org/10.5220/0007365700300037}, pages = {30 -- 37}, year = {2019}, language = {en} } @article{BertramAubrevilleDonovanetal.2021, author = {Bertram, Christof and Aubreville, Marc and Donovan, Taryn and Bartel, Alexander and Wilm, Frauke and Marzahl, Christian and Assenmacher, Charles-Antoine and Becker, Kathrin and Bennett, Mark and Corner, Sarah M. and Cossic, Brieuc and Denk, Daniela and Dettwiler, Martina and Garcia Gonzalez, Beatriz and Gurtner, Corinne and Haverkamp, Ann-Kathrin and Heier, Annabelle and Lehmbecker, Annika and Merz, Sophie and Noland, Erica L. and Plog, Stephanie and Schmidt, Anja and Sebastian, Franziska and Sledge, Dodd G. and Smedley, Rebecca C. and Tecilla, Marco and Thaiwong, Tuddow and Fuchs-Baumgartinger, Andrea and Meuten, Donald J. and Breininger, Katharina and Kiupel, Matti and Maier, Andreas and Klopfleisch, Robert}, title = {Computer-assisted mitotic count using a deep learning-based algorithm improves interobserver reproducibility and accuracy}, volume = {59}, journal = {Veterinary Pathology}, number = {2}, publisher = {Sage}, address = {London}, issn = {1544-2217}, doi = {https://doi.org/10.1177/03009858211067478}, pages = {211 -- 226}, year = {2021}, abstract = {The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or classifying mitotic figures (MFs). Recent progress in the field of artificial intelligence has allowed the development of high-performance algorithms that may improve standardization of the MC. As algorithmic predictions are not flawless, computer-assisted review by pathologists may ensure reliability. In the present study, we compared partial (MC-ROI preselection) and full (additional visualization of MF candidates and display of algorithmic confidence values) computer-assisted MC analysis to the routine (unaided) MC analysis by 23 pathologists for whole-slide images of 50 canine cutaneous mast cell tumors (ccMCTs). Algorithmic predictions aimed to assist pathologists in detecting mitotic hotspot locations, reducing omission of MFs, and improving classification against imposters. The interobserver consistency for the MC significantly increased with computer assistance (interobserver correlation coefficient, ICC = 0.92) compared to the unaided approach (ICC = 0.70). Classification into prognostic stratifications had a higher accuracy with computer assistance. The algorithmically preselected hotspot MC-ROIs had a consistently higher MCs than the manually selected MC-ROIs. Compared to a ground truth (developed with immunohistochemistry for phosphohistone H3), pathologist performance in detecting individual MF was augmented when using computer assistance (F1-score of 0.68 increased to 0.79) with a reduction in false negatives by 38\%. The results of this study demonstrate that computer assistance may lead to more reproducible and accurate MCs in ccMCTs.}, language = {en} } @article{MarzahlAubrevilleBertrametal.2020, author = {Marzahl, Christian and Aubreville, Marc and Bertram, Christof and Stayt, Jason and Jasensky, Anne-Katherine and Bartenschlager, Florian and Fragoso-Garcia, Marco and Barton, Ann K. and Elsemann, Svenja and Jabari, Samir and Krauth, Jens and Madhu, Prathmesh and Voigt, J{\"o}rn and Hill, Jenny and Klopfleisch, Robert and Maier, Andreas}, title = {Deep Learning-based quantification of pulmonary hemosiderophages in cytology slides}, volume = {10}, pages = {9795}, journal = {Scientific Reports}, publisher = {Springer Nature}, address = {London}, issn = {2045-2322}, doi = {https://doi.org/10.1038/s41598-020-65958-2}, year = {2020}, abstract = {Exercise-induced pulmonary hemorrhage (EIPH) is a common condition in sport horses with negative impact on performance. Cytology of bronchoalveolar lavage fluid by use of a scoring system is considered the most sensitive diagnostic method. Macrophages are classified depending on the degree of cytoplasmic hemosiderin content. The current gold standard is manual grading, which is however monotonous and time-consuming. We evaluated state-of-the-art deep learning-based methods for single cell macrophage classification and compared them against the performance of nine cytology experts and evaluated inter- and intra-observer variability. Additionally, we evaluated object detection methods on a novel data set of 17 completely annotated cytology whole slide images (WSI) containing 78,047 hemosiderophages. Our deep learning-based approach reached a concordance of 0.85, partially exceeding human expert concordance (0.68 to 0.86, mean of 0.73, SD of 0.04). Intra-observer variability was high (0.68 to 0.88) and inter-observer concordance was moderate (Fleiss' kappa = 0.67). Our object detection approach has a mean average precision of 0.66 over the five classes from the whole slide gigapixel image and a computation time of below two minutes. To mitigate the high inter- and intra-rater variability, we propose our automated object detection pipeline, enabling accurate, reproducible and quick EIPH scoring in WSI.}, language = {en} } @inproceedings{AubrevilleGoncalvesKnipferetal.2018, author = {Aubreville, Marc and Goncalves, Miguel and Knipfer, Christian and Oetter, Nicolai and W{\"u}rfl, Tobias and Neumann, Helmut and Stelzle, Florian and Bohr, Christopher and Maier, Andreas}, title = {Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images}, booktitle = {Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies}, subtitle = {A Cross-Site Robustness Assessment}, editor = {Wiebe, Sheldon and Gamboa, Hugo and Fred, Ana and Berm{\´u}dez i Badia, Sergi}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-278-3}, doi = {https://doi.org/10.5220/0006534700270034}, pages = {27 -- 34}, year = {2018}, abstract = {Deep learning technologies such as convolutional neural networks (CNN) provide powerful methods for image recognition and have recently been employed in the field of automated carcinoma detection in confocal laser endomicroscopy (CLE) images. CLE is a (sub-)surface microscopic imaging technique that reaches magnifications of up to 1000x and is thus suitable for in vivo structural tissue analysis. In this work, we aim to evaluate the prospects of a priorly developed deep learning-based algorithm targeted at the identification of oral squamous cell carcinoma with regard to its generalization to further anatomic locations of squamous cell carcinomas in the area of head and neck. We applied the algorithm on images acquired from the vocal fold area of five patients with histologically verified squamous cell carcinoma and presumably healthy control images of the clinically normal contra-lateral vocal cord. We find that the network trained on the oral cavity data reaches an accurac y of 89.45\% and an area-under-the-curve (AUC) value of 0.955, when applied on the vocal cords data. Compared to the state of the art, we achieve very similar results, yet with an algorithm that was trained on a completely disjunct data set. Concatenating both data sets yielded further improvements in cross-validation with an accuracy of 90.81\% and AUC of 0.970. In this study, for the first time to our knowledge, a deep learning mechanism for the identification of oral carcinomas using CLE Images could be applied to other disciplines in the area of head and neck. This study shows the prospect of the algorithmic approach to generalize well on other malignant entities of the head and neck, regardless of the anatomical location and furthermore in an examiner-independent manner.}, language = {en} } @unpublished{GanzMarzahlAmmelingetal.2024, author = {Ganz, Jonathan and Marzahl, Christian and Ammeling, Jonas and Rosbach, Emely and Richter, Barbara and Puget, Chlo{\´e} and Denk, Daniela and Demeter, Elena A. and Tabaran, Flaviu A. and Wasinger, Gabriel and Lipnik, Karoline and Tecilla, Marco and Valentine, Matthew J. and Dark, Michael and Abele, Niklas and Bolfa, Pompei and Erber, Ramona and Klopfleisch, Robert and Merz, Sophie and Donovan, Taryn and Jabari, Samir and Bertram, Christof and Breininger, Katharina and Aubreville, Marc}, title = {Information Mismatch in PHH3-Assisted Mitosis Annotation Leads to Interpretation Shifts in H\&E Slide Analysis}, titleParent = {Research Square}, publisher = {Research Square}, address = {Durham}, doi = {https://doi.org/10.21203/rs.3.rs-4900505/v1}, year = {2024}, abstract = {The count of mitotic figures (MFs) observed in hematoxylin and eosin (H\&E)-stained slides is an important prognostic marker, as it is a measure for tumor cell proliferation. However, the identification of MFs has a known low inter-rater agreement. In a computer-aided setting, deep learning algorithms can help to mitigate this, but they require large amounts of annotated data for training and validation. Furthermore, label noise introduced during the annotation process may impede the algorithms' performance. Unlike H\&E, where identification of MFs is based mainly on morphological features, the mitosis-specific antibody phospho-histone H3 (PHH3) specifically highlights MFs. Counting MFs on slides stained against PHH3 leads to higher agreement among raters and has therefore recently been used as a ground truth for the annotation of MFs in H\&E. However, as PHH3 facilitates the recognition of cells indistinguishable from H\&E staining alone, the use of this ground truth could potentially introduce an interpretation shift and even label noise into the H\&E-related dataset, impacting model performance. This study analyzes the impact of PHH3-assisted MF annotation on inter-rater reliability and object level agreement through an extensive multi-rater experiment. Subsequently, MF detectors, including a novel dual-stain detector, were evaluated on the resulting datasets to investigate the influence of PHH3-assisted labeling on the models' performance. We found that the annotators' object-level agreement significantly increased when using PHH3-assisted labeling (F1: 0.53 to 0.74). However, this enhancement in label consistency did not translate to improved performance for H\&E-based detectors, neither during the training phase nor the evaluation phase. Conversely, the dual-stain detector was able to benefit from the higher consistency. This reveals an information mismatch between the H\&E and PHH3-stained images as the cause of this effect, which renders PHH3-assisted annotations not well-aligned for use with H\&E-based detectors. Based on our findings, we propose an improved PHH3-assisted labeling procedure.}, language = {en} } @article{AubrevilleBertramMarzahletal.2020, author = {Aubreville, Marc and Bertram, Christof and Marzahl, Christian and Gurtner, Corinne and Dettwiler, Martina and Schmidt, Anja and Bartenschlager, Florian and Merz, Sophie and Fragoso-Garcia, Marco and Kershaw, Olivia and Klopfleisch, Robert and Maier, Andreas}, title = {Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region}, volume = {10}, pages = {16447}, journal = {Scientific reports}, publisher = {Springer Nature}, address = {London}, issn = {2045-2322}, doi = {https://doi.org/10.1038/s41598-020-73246-2}, year = {2020}, abstract = {Manual count of mitotic figures, which is determined in the tumor region with the highest mitotic activity, is a key parameter of most tumor grading schemes. It can be, however, strongly dependent on the area selection due to uneven mitotic figure distribution in the tumor section. We aimed to assess the question, how significantly the area selection could impact the mitotic count, which has a known high inter-rater disagreement. On a data set of 32 whole slide images of H\&E-stained canine cutaneous mast cell tumor, fully annotated for mitotic figures, we asked eight veterinary pathologists (five board-certified, three in training) to select a field of interest for the mitotic count. To assess the potential difference on the mitotic count, we compared the mitotic count of the selected regions to the overall distribution on the slide. Additionally, we evaluated three deep learning-based methods for the assessment of highest mitotic density: In one approach, the model would directly try to predict the mitotic count for the presented image patches as a regression task. The second method aims at deriving a segmentation mask for mitotic figures, which is then used to obtain a mitotic density. Finally, we evaluated a two-stage object-detection pipeline based on state-of-the-art architectures to identify individual mitotic figures. We found that the predictions by all models were, on average, better than those of the experts. The two-stage object detector performed best and outperformed most of the human pathologists on the majority of tumor cases. The correlation between the predicted and the ground truth mitotic count was also best for this approach (0.963-0.979). Further, we found considerable differences in position selection between pathologists, which could partially explain the high variance that has been reported for the manual mitotic count. To achieve better inter-rater agreement, we propose to use a computer-based area selection for support of the pathologist in the manual mitotic count.}, language = {en} } @unpublished{AmmelingHeckerGanzetal.2023, author = {Ammeling, Jonas and Hecker, Moritz and Ganz, Jonathan and Donovan, Taryn and Klopfleisch, Robert and Bertram, Christof and Breininger, Katharina and Aubreville, Marc}, title = {Automated Volume Corrected Mitotic Index Calculation Through Annotation-Free Deep Learning using Immunohistochemistry as Reference Standard}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2311.08949}, year = {2023}, abstract = {The volume-corrected mitotic index (M/V-Index) was shown to provide prognostic value in invasive breast carcinomas. However, despite its prognostic significance, it is not established as the standard method for assessing aggressive biological behaviour, due to the high additional workload associated with determining the epithelial proportion. In this work, we show that using a deep learning pipeline solely trained with an annotation-free, immunohistochemistry-based approach, provides accurate estimations of epithelial segmentation in canine breast carcinomas. We compare our automatic framework with the manually annotated M/V-Index in a study with three board-certified pathologists. Our results indicate that the deep learning-based pipeline shows expert-level performance, while providing time efficiency and reproducibility.}, language = {en} } @inbook{MuallaAubrevilleMaier2018, author = {Mualla, Firas and Aubreville, Marc and Maier, Andreas}, title = {Microscopy}, booktitle = {Medical Imaging Systems: An Introductory Guide}, editor = {Maier, Andreas and Steidl, Stefan and Christlein, Vincent and Hornegger, Joachim}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-96520-8}, doi = {https://doi.org/10.1007/978-3-319-96520-8_5}, pages = {69 -- 90}, year = {2018}, abstract = {We perceive the physical world around us using our eyes, but only down to a certain limit. Objects with a diameter smaller than 75 μm cannot be recognized by the naked eye, and due to this reason, they remained undiscovered for the most of human history.}, language = {en} } @unpublished{AmmelingSchmidtGanzetal.2022, author = {Ammeling, Jonas and Schmidt, Lars-Henning and Ganz, Jonathan and Niedermair, Tanja and Brochhausen-Delius, Christoph and Schulz, Christian and Breininger, Katharina and Aubreville, Marc}, title = {Attention-based Multiple Instance Learning for Survival Prediction on Lung Cancer Tissue Microarrays}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2212.07724}, year = {2022}, abstract = {Attention-based multiple instance learning (AMIL) algorithms have proven to be successful in utilizing gigapixel whole-slide images (WSIs) for a variety of different computational pathology tasks such as outcome prediction and cancer subtyping problems. We extended an AMIL approach to the task of survival prediction by utilizing the classical Cox partial likelihood as a loss function, converting the AMIL model into a nonlinear proportional hazards model. We applied the model to tissue microarray (TMA) slides of 330 lung cancer patients. The results show that AMIL approaches can handle very small amounts of tissue from a TMA and reach similar C-index performance compared to established survival prediction methods trained with highly discriminative clinical factors such as age, cancer grade, and cancer stage.}, language = {en} } @unpublished{StoeveAubrevilleOetteretal.2018, author = {Stoeve, Maike and Aubreville, Marc and Oetter, Nicolai and Knipfer, Christian and Neumann, Helmut and Stelzle, Florian and Maier, Andreas}, title = {Motion Artifact Detection in Confocal Laser Endomicroscopy Images}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.1711.01117}, year = {2018}, abstract = {Confocal Laser Endomicroscopy (CLE), an optical imaging technique allowing non-invasive examination of the mucosa on a (sub)- cellular level, has proven to be a valuable diagnostic tool in gastroenterology and shows promising results in various anatomical regions including the oral cavity. Recently, the feasibility of automatic carcinoma detection for CLE images of sufficient quality was shown. However, in real world data sets a high amount of CLE images is corrupted by artifacts. Amongst the most prevalent artifact types are motion-induced image deteriorations. In the scope of this work, algorithmic approaches for the automatic detection of motion artifact-tainted image regions were developed. Hence, this work provides an important step towards clinical applicability of automatic carcinoma detection. Both, conventional machine learning and novel, deep learning-based approaches were assessed. The deep learning-based approach outperforms the conventional approaches, attaining an AUC of 0.90.}, language = {en} } @unpublished{AubrevillePanSievertetal.2023, author = {Aubreville, Marc and Pan, Zhaoya and Sievert, Matti and Ammeling, Jonas and Ganz, Jonathan and Oetter, Nicolai and Stelzle, Florian and Frenken, Ann-Kathrin and Breininger, Katharina and Goncalves, Miguel}, title = {Few Shot Learning for the Classification of Confocal Laser Endomicroscopy Images of Head and Neck Tumors}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2311.07216}, year = {2023}, abstract = {The surgical removal of head and neck tumors requires safe margins, which are usually confirmed intraoperatively by means of frozen sections. This method is, in itself, an oversampling procedure, which has a relatively low sensitivity compared to the definitive tissue analysis on paraffin-embedded sections. Confocal laser endomicroscopy (CLE) is an in-vivo imaging technique that has shown its potential in the live optical biopsy of tissue. An automated analysis of this notoriously difficult to interpret modality would help surgeons. However, the images of CLE show a wide variability of patterns, caused both by individual factors but also, and most strongly, by the anatomical structures of the imaged tissue, making it a challenging pattern recognition task. In this work, we evaluate four popular few shot learning (FSL) methods towards their capability of generalizing to unseen anatomical domains in CLE images. We evaluate this on images of sinunasal tumors (SNT) from five patients and on images of the vocal folds (VF) from 11 patients using a cross-validation scheme. The best respective approach reached a median accuracy of 79.6\% on the rather homogeneous VF dataset, but only of 61.6\% for the highly diverse SNT dataset. Our results indicate that FSL on CLE images is viable, but strongly affected by the number of patients, as well as the diversity of anatomical patterns.}, language = {en} } @inproceedings{SchlagowskiHergetHeimerletal.2024, author = {Schlagowski, Ruben and Herget, Frederick and Heimerl, Niklas and Hammerl, Maximilian and Huber, Tobias and Zwolsky, Pamina and Gruca, Jan and Andr{\´e}, Elisabeth}, title = {From a Social POV: The Impact of Point of View on Player Behavior, Engagement, and Experience in a Serious Social Simulation Game}, booktitle = {Proceedings of the 19th International Conference on the Foundations of Digital Games, FDG 2024}, editor = {Smith, Gillian and Whitehead, Jim and Samuel, Ben and Spiel, Katta and van Rozen, Riemer}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-0955-5}, doi = {https://doi.org/10.1145/3649921.3649936}, year = {2024}, abstract = {Multiplayer games with social aspects vary widely regarding client design, e.g., point of view or camera perspective. While design paradigms usually arise from gold standards that are set by previously successful games in the industry, the impact of such paradigms is under-researched for games that serve as scientific instruments, e.g., to research social behavior. Intending to investigate how such games should be designed, we built two multiplayer clients with the same game logic, one using a first-person point of view, while the other includes a top-down camera perspective. Then, we conducted an online user study in which players tested these game clients in extensive multiplayer sessions. Analyzing speech time, in-game logs, questionnaires, and qualitative feedback, we look at the perspectives' impact on player behavior, engagement, and game experience in a scientific or "serious games" context. In addition, we have made our designed game UNISON and both clients available as open source to facilitate future empirical social science research.}, language = {en} } @unpublished{PerniasRampasAubreville2023, author = {Pernias, Pablo and Rampas, Dominic and Aubreville, Marc}, title = {W{\"u}rstchen: Efficient Pretraining of Text-to-Image Models}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2306.00637}, year = {2023}, abstract = {We introduce Wuerstchen, a novel technique for text-to-image synthesis that unites competitive performance with unprecedented cost-effectiveness and ease of training on constrained hardware. Building on recent advancements in machine learning, our approach, which utilizes latent diffusion strategies at strong latent image compression rates, significantly reduces the computational burden, typically associated with state-of-the-art models, while preserving, if not enhancing, the quality of generated images. Wuerstchen achieves notable speed improvements at inference time, thereby rendering real-time applications more viable. One of the key advantages of our method lies in its modest training requirements of only 9,200 GPU hours, slashing the usual costs significantly without compromising the end performance. In a comparison against the state-of-the-art, we found the approach to yield strong competitiveness. This paper opens the door to a new line of research that prioritizes both performance and computational accessibility, hence democratizing the use of sophisticated AI technologies. Through Wuerstchen, we demonstrate a compelling stride forward in the realm of text-to-image synthesis, offering an innovative path to explore in future research.}, language = {en} } @book{ElstermannFleischmannMoseretal.2026, author = {Elstermann, Matthes and Fleischmann, Albert and Moser, Christoph and Oppl, Stefan and Schmidt, Werner and Stary, Christian}, title = {Contextual Process Digitalization}, subtitle = {Changing Perspectives - Design Thinking - Value-Led Design}, edition = {Second Edition}, publisher = {Springer}, address = {Cham}, isbn = {978-3-032-06901-6}, doi = {https://doi.org/10.1007/978-3-032-06901-6}, pages = {XII, 343}, year = {2026}, abstract = {This open access book presents an overview and step-by-step explanation of process management. It starts with the individual participants' perspectives on their work in a process and its structuring and harmonization, and then moves on to its specification in a model and how it is embedded in the organizational and IT environment of the company. Lastly, the book examines the joint processing of instances in the resulting socio-technical systems. A corresponding illustration, which expands with the overview, enables readers to gain a comprehensive understanding of business process management. The book presents various facets of business process management from the perspective of the participants, and introduces a selection of models that have proved useful in practice. The design of such models supports the transition from a more-or-less unstructured or unsatisfactory way of working to a structured process that corresponds to the ideas of the company and its customers. For this second edition, several new sections dealing with the integration of IoT processes, artificial intelligence, and social behavior patterns in process mining, a whole chapter on implementation and operation, and three new case studies were added. The book is intended for professionals in industry as well as students in the field of business information systems who are looking for guidelines on how to discover, create and implement real-world processes.}, language = {en} } @article{WanZhaoWiedholzetal.2025, author = {Wan, Lei and Zhao, Jianxin and Wiedholz, Andreas and Bied, Manuel and Martinez de Lucena, Mateus and Jagtap, Abhishek Dinkar and Festag, Andreas and Fr{\"o}hlich, Ant{\^o}nio and Keen, Hannan Ejaz and Vinel, Alexey}, title = {A Systematic Literature Review on Vehicular Collaborative Perception—A Computer Vision Perspective}, volume = {27}, journal = {IEEE Transactions on Intelligent Transportation Systems}, number = {1}, publisher = {IEEE}, address = {New York}, issn = {1558-0016}, doi = {https://doi.org/10.1109/TITS.2025.3631141}, pages = {81 -- 118}, year = {2025}, abstract = {The effectiveness of autonomous vehicles relies on reliable perception capabilities. Despite significant advancements in artificial intelligence and sensor fusion technologies, current single-vehicle perception systems continue to encounter limitations, notably visual occlusions and limited long-range detection capabilities. Collaborative Perception (CP), enabled by Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, has emerged as a promising solution to mitigate these issues and enhance the reliability of autonomous systems. Beyond advancements in communication, the computer vision community is increasingly focusing on improving vehicular perception through collaborative approaches. However, a systematic literature review that thoroughly examines existing work and reduces subjective bias is still lacking. Such a systematic approach helps identify research gaps, recognize common trends across studies, and inform future research directions. In response, this study follows the PRISMA 2020 guidelines and includes 106 peer-reviewed articles. These publications are analyzed based on modalities, collaboration schemes, and key perception tasks. Through a comparative analysis, this review illustrates how different methods address practical issues such as pose errors, temporal latency, communication constraints, domain shifts, heterogeneity, and adversarial attacks. Furthermore, it critically examines evaluation methodologies, highlighting a misalignment between current metrics and CP's fundamental objectives. By delving into all relevant topics in-depth, this review offers valuable insights into challenges, opportunities, and risks, serving as a reference for advancing research in vehicular collaborative perception.}, language = {en} } @article{MertesHuberWeitzetal.2022, author = {Mertes, Silvan and Huber, Tobias and Weitz, Katharina and Heimerl, Alexander and Andr{\´e}, Elisabeth}, title = {GANterfactual—Counterfactual Explanations for Medical Non-experts Using Generative Adversarial Learning}, volume = {5}, pages = {825565}, journal = {Frontiers in Artificial Intelligence}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2624-8212}, doi = {https://doi.org/10.3389/frai.2022.825565}, year = {2022}, abstract = {With the ongoing rise of machine learning, the need for methods for explaining decisions made by artificial intelligence systems is becoming a more and more important topic. Especially for image classification tasks, many state-of-the-art tools to explain such classifiers rely on visual highlighting of important areas of the input data. Contrary, counterfactual explanation systems try to enable a counterfactual reasoning by modifying the input image in a way such that the classifier would have made a different prediction. By doing so, the users of counterfactual explanation systems are equipped with a completely different kind of explanatory information. However, methods for generating realistic counterfactual explanations for image classifiers are still rare. Especially in medical contexts, where relevant information often consists of textural and structural information, high-quality counterfactual images have the potential to give meaningful insights into decision processes. In this work, we present GANterfactual, an approach to generate such counterfactual image explanations based on adversarial image-to-image translation techniques. Additionally, we conduct a user study to evaluate our approach in an exemplary medical use case. Our results show that, in the chosen medical use-case, counterfactual explanations lead to significantly better results regarding mental models, explanation satisfaction, trust, emotions, and self-efficacy than two state-of-the art systems that work with saliency maps, namely LIME and LRP.}, language = {en} } @unpublished{MertesKarleHuberetal.2022, author = {Mertes, Silvan and Karle, Christina and Huber, Tobias and Weitz, Katharina and Schlagowski, Ruben and Andr{\´e}, Elisabeth}, title = {Alterfactual Explanations - The Relevance of Irrelevance for Explaining AI Systems}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2207.09374}, year = {2022}, abstract = {Explanation mechanisms from the field of Counterfactual Thinking are a widely-used paradigm for Explainable Artificial Intelligence (XAI), as they follow a natural way of reasoning that humans are familiar with. However, all common approaches from this field are based on communicating information about features or characteristics that are especially important for an AI's decision. We argue that in order to fully understand a decision, not only knowledge about relevant features is needed, but that the awareness of irrelevant information also highly contributes to the creation of a user's mental model of an AI system. Therefore, we introduce a new way of explaining AI systems. Our approach, which we call Alterfactual Explanations, is based on showing an alternative reality where irrelevant features of an AI's input are altered. By doing so, the user directly sees which characteristics of the input data can change arbitrarily without influencing the AI's decision. We evaluate our approach in an extensive user study, revealing that it is able to significantly contribute to the participants' understanding of an AI. We show that alterfactual explanations are suited to convey an understanding of different aspects of the AI's reasoning than established counterfactual explanation methods.}, language = {en} } @book{FleischmannOpplSchmidtetal.2020, author = {Fleischmann, Albert and Oppl, Stefan and Schmidt, Werner and Stary, Christian}, title = {Contextual Process Digitalization}, subtitle = {Changing Perspectives - Design Thinking - Value-Led Design}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-38299-5}, doi = {https://doi.org/10.1007/978-3-030-38300-8}, pages = {X, 275}, year = {2020}, abstract = {This open access book presents an overview and step-by-step explanation of process management. It starts with the individual participants' perspectives on their work in a process and its structuring and harmonization, and then moves on to its specification in a model and how it is embedded in the organizational and IT environment of the company. Lastly, the book examines the joint processing of instances in the resulting socio-technical systems. A corresponding illustration, which expands with the overview, enables readers to gain a comprehensive understanding of business process management. The book presents various facets of business process management from the perspective of the participants, and introduces a selection of models that have proved useful in practice. The design of such models supports the transition from a more-or-less unstructured or unsatisfactory way of working to a structured process that corresponds to the ideas of the company and its customers. The book is intended for professionals in industry as well as students in the field of business information systems who are looking for guidelines on how to discover, create and implement real-world processes.}, language = {en} } @article{GregorBauderKirstenVidaldeOliveiraetal.2025, author = {Gregor, Markus and Bauder, Maximilian and Kirsten Vidal de Oliveira, Aline and Mast, Pascal and R{\"u}ther, Ricardo and Schweiger, Hans-Georg}, title = {Approaches for Lifetime Prediction of Vehicle Traction Battery Systems During a Technical Inspection: A Systematic Review}, volume = {17}, pages = {3}, journal = {World Electric Vehicle Journal}, number = {1}, publisher = {MDPI}, address = {Basel}, issn = {2032-6653}, doi = {https://doi.org/10.3390/wevj17010003}, year = {2025}, abstract = {Creating trust in society for new technologies, such as a new types of powertrains, and making them marketable requires transparent, neutral, and independent technical verification. This is crucial for the acceptance and success of electrified vehicles in the used car markets. A key component of electric vehicles is the traction battery, whose current and future condition, particularly regarding aging, determines its residual value and safe operation. This review aims to identify and evaluate methods for predicting the lifetime of onboard traction batteries, focusing on their applicability in technical inspections. A systematic literature and patent review was conducted using targeted keywords, yielding 22 patents and 633 publications. From these, 150 distinct lifetime prediction methods were extracted and categorized into a four-level mind map. These methods are summarized, cited, and structured in detailed tables. The relationships between approaches are explained to clarify the current research landscape. Long Short-Term Memory, Convolutional Neural Networks, and Particle Filters were identified as the most frequently used techniques. However, no methods were found suitable for predicting the lifetime of traction batteries during technical vehicle inspections, which operate under short test durations, limited data access, and diverse real-world operating conditions. Most studies focused on cell-level testing and did not address complete battery systems in operational vehicles. This gap highlights the need for applied research and the development of practical methods to support battery assessment in real-world conditions. Advancing this field is essential to foster confidence in battery systems and enable a sustainable transition to electromobility.}, language = {en} } @article{BienertRegnet2025, author = {Bienert, J{\"o}rg and Regnet, Simon}, title = {Stability Analysis for an Ultra-Lightweight Glider Airplane with Electric Driven Two-Blade Propeller}, volume = {9}, pages = {3}, journal = {Vibration}, number = {1}, publisher = {MDPI}, address = {Basel}, issn = {2571-631X}, doi = {https://doi.org/10.3390/vibration9010003}, year = {2025}, abstract = {Safety is the most important requirement in flight operations. This also affects the application for an extreme lightweight glider in this paper. Essential properties are the target weight below 120 kgand the electric propulsion. The unsymmetric inertia from the two-blade propeller at the rear in combination with the light and flexible aluminium tube support makes it necessary to investigate the risk of mechanical instability. Starting from the equations of motion, the time-variant system matrices are set up. The simulation of Floquet multiplier and Hill's hyper-eigenvalue problem provide the necessary information about the system stability. The conclusion is that the potential instability due to structural damping in the observed system can be avoided in the range of operation. The damping, experimentally determined by approximately 2\%, is sufficient.}, language = {en} } @book{FleischmannOpplSchmidtetal.2018, author = {Fleischmann, Albert and Oppl, Stefan and Schmidt, Werner and Stary, Christian}, title = {Ganzheitliche Digitalisierung von Prozessen}, subtitle = {Perspektivenwechsel - Design Thinking - Wertegeleitete Interaktion}, publisher = {Springer Vieweg}, address = {Wiesbaden}, isbn = {978-3-658-22647-3}, doi = {https://doi.org/10.1007/978-3-658-22648-0}, pages = {X, 254}, year = {2018}, abstract = {In diesem Open-Access-Buch wird das Gesch{\"a}ftsprozessmanagement als ein ganzheitlicher Prozess begriffen, der der Mitwirkung aller Stakeholder bedarf. Denn das traditionelle Business Process Engineering st{\"o}ßt heute angesichts der Digitalisierung und der dynamischen Entwicklung von Organisationen immer mehr an seine Grenzen, beispielsweise bez{\"u}glich Agilit{\"a}t. Um nun das Wesen von Aufgaben und Abl{\"a}ufen in Organisationen zu erfassen, schlagen die Autoren einen Perspektivwechsel vor: das Denken in Kommunikationsprozessen. Dieses Konzept l{\"a}sst sich wirtschaftlich, organisatorisch und technisch ohne einschl{\"a}gige Vorkenntnisse umsetzen. Leserinnen und Leser finden in dem Buch konkrete Handlungsanleitungen f{\"u}r die Digitalisierung von organisationsrelevanten Abl{\"a}ufen. Daneben liefern die Autoren Einblicke in die Systemtheorie und in das Design Thinking. Ihr Ziel ist, Konzepte einfach und verst{\"a}ndlich zu erl{\"a}utern, ohne dabei komplexe Zusammenh{\"a}nge zu vernachl{\"a}ssigen. Dank ausf{\"u}hrlicher Konzeptdarstellung und Ausfl{\"u}ge in die Theorie mit Beispielen aus der Praxis, eignet es sich f{\"u}r Studierende und f{\"u}r Wissenschaftler genauso wie f{\"u}r Praktiker. Entwickler und andere Fachkr{\"a}fte aus den Bereichen Operatives Management, Gesch{\"a}ftsprozessmanagement, Organisationsentwicklung, Qualit{\"a}tsmanagement, Wissensmanagement werden sich von der {\"U}bersichtlichkeit und dem Nutzwert angesprochen f{\"u}hlen. Der Inhalt - Modelle - Modellierungssprachen - Vorgehensweise von der Modellbildung zur Digitalisierung - Vorbereitung der Prozessimplementierung - Umsetzung - Praxisbeispiel}, language = {de} } @article{FleischmannSchmidtStary2015, author = {Fleischmann, Albert and Schmidt, Werner and Stary, Christian}, title = {Dynamic Socio-technical System Design based on Stakeholder Interaction}, volume = {2015}, journal = {Complex Systems Informatics and Modeling Quarterly (CSIMQ)}, number = {3}, publisher = {Technische Universit{\"a}t Riga}, address = {Riga}, issn = {2255-9922}, doi = {https://doi.org/10.7250/csimq.2015-3.04}, pages = {63 -- 83}, year = {2015}, abstract = {In order to directly involve stakeholders in socio-technical system design, we argue for streamlining executable process specifications with business process modeling. Due to current agility requirements of organizations, socio-technical system development is considered one of the key activities of members of the organizations. Dynamic process adaptation enable handling the volatility of business operation and IT infrastructure. Subject-oriented process representations are key enablers to dynamic adaptation due to their capability for stakeholders to create directly executable models. In this way stakeholder can be involved in change management pro-actively. Subject-oriented models (i) represent all relevant features required for system control and decision making, and (ii) are executable on demand. This effectiveness enables organizational change in a creative and efficient way, while establishing innovative design and change management tools. Subject-oriented Business Process Management capabilities are reflected in this realm revealing benefits and potential for further research.}, language = {en} }