@article{RillSchuderer, author = {Rill, Georg and Schuderer, Matthias}, title = {A Second-Order Dynamic Friction Model Compared to Commercial Stick-Slip Models}, series = {Modelling}, volume = {4}, journal = {Modelling}, number = {3}, publisher = {MDPI}, issn = {2673-3951}, doi = {10.3390/modelling4030021}, pages = {366 -- 381}, abstract = {Friction has long been an important issue in multibody dynamics. Static friction models apply appropriate regularization techniques to convert the stick inequality and the non-smooth stick-slip transition of Coulomb's approach into a continuous and smooth function of the sliding velocity. However, a regularized friction force is not able to maintain long-term stick. That is why dynamic friction models were developed in recent decades. The friction force depends herein not only on the sliding velocity but also on internal states. The probably best-known representative, the LuGre friction model, is based on a fictitious bristle but realizes a too-simple approximation. The recently published second-order dynamic friction model describes the dynamics of a fictitious bristle more accurately. It is based on a regularized friction force characteristic, which is continuous and smooth but can maintain long-term stick due to an appropriate shift in the regularization. Its performance is compared here to stick-slip friction models, developed and launched not long ago by commercial multibody software packages. The results obtained by a virtual friction test-bench and by a more practical festoon cable system are very promising. Thus, the second-order dynamic friction model may serve not only as an alternative to the LuGre model but also to commercial stick-slip models.}, language = {en} } @article{HausladenSchelsAsgharzadeetal., author = {Hausladen, Matthias and Schels, Andreas and Asgharzade, Ali and Buchner, Philipp and Bartl, Mathias and Wohlfartsst{\"a}tter, Dominik and Edler, Simon and Bachmann, Michael and Schreiner, Rupert}, title = {Investigation of Influencing Factors on the Measurement Signal of a CMOS Image Sensor for Measuring Field Emission Currents}, series = {Sensors}, volume = {25}, journal = {Sensors}, number = {5}, publisher = {MDPI}, doi = {10.3390/s25051529}, pages = {17}, language = {en} } @article{MarkovGlazerElbeSchliermann, author = {Markov-Glazer, Alon and Elbe, Anne-Marie and Schliermann, Rainer}, title = {The use of psychological skills in deaflympic sport}, series = {European Journal of Adapted Physical Activity}, volume = {17}, journal = {European Journal of Adapted Physical Activity}, number = {15}, publisher = {European Federation of Adapted Physical Activity}, address = {Olomouc}, doi = {10.5507/euj.2024.012}, pages = {13}, abstract = {This study explores the use of psychological skills among Deaflympic athletes and aims to provide initial insights into sport psychology practices in this overlooked population. To this end, the frequency of psychological skills' usage, usage patterns, and differences between subgroups were examined within this population. The Test of Performance Strategies (TOPS) was administered to 84 German Deaflympic athletes (mean age = 28; 27\% female) along with biographical questions (e.g., hearing status). The findings indicate that Deaflympic athletes regularly utilize psychological skills in training and competition, displaying similar usage to that of Olympic athletes. However, only a minority of Deaflympic athletes train their skills with professional consultants. Additionally, relaxation techniques were employed rarely in comparison to the other investigated skills. This study's findings contribute to the foundation of sport psychology research with Deaflympic athletes and underscore the need for a differentiated approach in tailoring interventions for this population.}, language = {en} } @article{SchwarzPastoetterTranetal., author = {Schwarz, Tobias and Past{\"o}tter, Angelina and Tran, T. H. and Schlosser, Marc and Kaulen, Corinna and Lechner, Alfred and Slabon, A. and Kammler, Martin}, title = {Effect of temperature on the growth of Cupric and Cuprous Nanoparticles in a wet chemical synthesis}, series = {Materials Letters}, volume = {381}, journal = {Materials Letters}, publisher = {Springer Nature}, doi = {10.1016/j.matlet.2024.137672}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-79279}, abstract = {Cuprous oxide (Cu2O) and cupric oxide (CuO) particles were synthesized using a wet chemical surfactant free method at different synthesis temperatures from 25 °C to 60 °C. Morphology, size, and chemical composition of the prepared Cu2O particles were analyzed by FESEM, PXRD, and UV-vis. We discovered that the chemical composition of the Cu2O particles remained unaffected by the synthesis temperature. However, morphology and size of the particles showed a strong temperature dependency. This could be attributed to the temperature induced formation of CuO species from the copper hydroxide (Cu(OH)2) precursor which also functions as copper precursor for the Cu2O particle growth. The cupric oxide species was determined to be the main cause for the formation of micrometer sized particles, whereas with the Cu(OH)2 precursor species for the Cu2O particles nanocubes with smaller edge lengths as well as octahedrons were obtained.}, language = {en} } @article{VoglSchulzSchaefferetal., author = {Vogl, Yannick and Schulz, Carsten and Schaeffer, Thomas and Geiger, Benjamin}, title = {Prediction of the wear behavior of a conveyor belt with flexible rollers}, series = {Multibody System Dynamics}, journal = {Multibody System Dynamics}, publisher = {Springer}, address = {Cham}, issn = {1384-5640}, doi = {10.1007/s11044-025-10097-7}, pages = {16}, abstract = {This paper introduces a method to predict wear behavior in conveyor belt systems using a lumped mass modeling approach. While previous research has focused primarily on lateral belt walking, this study shifts attention to belt deformation and its associated wear. Both significantly affect system efficiency and component lifespan. The authors propose using local frictional power as a wear indicator, leveraging its direct relation to frictional work in established wear models. To solely demonstrate the method, the study simulates a conveyor belt with three flexible rollers and a deformable belt modeled through rigid spheres connected by spring-damper elements. The authors visualize frictional power density across the belt width, distinguishing between running and transverse directions. The results demonstrate that the frictional power distribution depends heavily on discretization quality, particularly due to the polygon effect inherent in the lumped mass approach. A convergence analysis reveals the minimum necessary discretization of the belt, ensuring reliable qualitative results. To support the credibility of the work, this study compares theoretical expectations and initial wear observations from a real belt with the results from the shown approach. The plausibility check already shows promising results. The proposed methodology provides an adaptable framework to evaluate wear in belt-like structures. It can be readily adapted to a variety of multibody dynamics applications and integrated into larger MBS models that include the overall drivetrain and engine control. Future work will focus on refining discretization strategies and contact models, as well as validation of the wear model to enable quantitative predictions.}, language = {en} } @article{MendelRauberSouzaJretal., author = {Mendel, Robert and Rauber, David and Souza Jr., Luis Antonio de and Papa, Jo{\~a}o Paulo and Palm, Christoph}, title = {Error-Correcting Mean-Teacher: Corrections instead of consistency-targets applied to semi-supervised medical image segmentation}, series = {Computers in Biology and Medicine}, volume = {154}, journal = {Computers in Biology and Medicine}, number = {March}, publisher = {Elsevier}, issn = {0010-4825}, doi = {10.1016/j.compbiomed.2023.106585}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-57790}, pages = {13}, abstract = {Semantic segmentation is an essential task in medical imaging research. Many powerful deep-learning-based approaches can be employed for this problem, but they are dependent on the availability of an expansive labeled dataset. In this work, we augment such supervised segmentation models to be suitable for learning from unlabeled data. Our semi-supervised approach, termed Error-Correcting Mean-Teacher, uses an exponential moving average model like the original Mean Teacher but introduces our new paradigm of error correction. The original segmentation network is augmented to handle this secondary correction task. Both tasks build upon the core feature extraction layers of the model. For the correction task, features detected in the input image are fused with features detected in the predicted segmentation and further processed with task-specific decoder layers. The combination of image and segmentation features allows the model to correct present mistakes in the given input pair. The correction task is trained jointly on the labeled data. On unlabeled data, the exponential moving average of the original network corrects the student's prediction. The combined outputs of the students' prediction with the teachers' correction form the basis for the semi-supervised update. We evaluate our method with the 2017 and 2018 Robotic Scene Segmentation data, the ISIC 2017 and the BraTS 2020 Challenges, a proprietary Endoscopic Submucosal Dissection dataset, Cityscapes, and Pascal VOC 2012. Additionally, we analyze the impact of the individual components and examine the behavior when the amount of labeled data varies, with experiments performed on two distinct segmentation architectures. Our method shows improvements in terms of the mean Intersection over Union over the supervised baseline and competing methods. Code is available at https://github.com/CloneRob/ECMT.}, language = {en} } @article{GrassmannMengelkampBrandletal., author = {Graßmann, Felix and Mengelkamp, Judith and Brandl, Caroline and Harsch, Sebastian and Zimmermann, Martina E. and Linkohr, Birgit and Peters, Annette and Heid, Iris M. and Palm, Christoph and Weber, Bernhard H. F.}, title = {A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography}, series = {Ophtalmology}, volume = {125}, journal = {Ophtalmology}, number = {9}, publisher = {Elsevier}, doi = {10.1016/j.ophtha.2018.02.037}, pages = {1410 -- 1420}, abstract = {Purpose Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding disease risk and progression, several systems based on color fundus photographs are known. Most of these require in-depth and time-consuming analysis of fundus images. Herein, we present an automated computer-based classification algorithm. Design Algorithm development for AMD classification based on a large collection of color fundus images. Validation is performed on a cross-sectional, population-based study. Participants. We included 120 656 manually graded color fundus images from 3654 Age-Related Eye Disease Study (AREDS) participants. AREDS participants were >55 years of age, and non-AMD sight-threatening diseases were excluded at recruitment. In addition, performance of our algorithm was evaluated in 5555 fundus images from the population-based Kooperative Gesundheitsforschung in der Region Augsburg (KORA; Cooperative Health Research in the Region of Augsburg) study. Methods. We defined 13 classes (9 AREDS steps, 3 late AMD stages, and 1 for ungradable images) and trained several convolution deep learning architectures. An ensemble of network architectures improved prediction accuracy. An independent dataset was used to evaluate the performance of our algorithm in a population-based study. Main Outcome Measures. κ Statistics and accuracy to evaluate the concordance between predicted and expert human grader classification. Results. A network ensemble of 6 different neural net architectures predicted the 13 classes in the AREDS test set with a quadratic weighted κ of 92\% (95\% confidence interval, 89\%-92\%) and an overall accuracy of 63.3\%. In the independent KORA dataset, images wrongly classified as AMD were mainly the result of a macular reflex observed in young individuals. By restricting the KORA analysis to individuals >55 years of age and prior exclusion of other retinopathies, the weighted and unweighted κ increased to 50\% and 63\%, respectively. Importantly, the algorithm detected 84.2\% of all fundus images with definite signs of early or late AMD. Overall, 94.3\% of healthy fundus images were classified correctly. Conclusions Our deep learning algoritm revealed a weighted κ outperforming human graders in the AREDS study and is suitable to classify AMD fundus images in other datasets using individuals >55 years of age.}, subject = {Senile Makuladegeneration}, language = {en} } @article{MaierPerretSimonetal., author = {Maier, Johannes and Perret, Jerome and Simon, Martina and Schmitt-R{\"u}th, Stephanie and Wittenberg, Thomas and Palm, Christoph}, title = {Force-feedback assisted and virtual fixtures based K-wire drilling simulation}, series = {Computers in Biology and Medicine}, volume = {114}, journal = {Computers in Biology and Medicine}, publisher = {Elsevier}, doi = {10.1016/j.compbiomed.2019.103473}, pages = {1 -- 10}, abstract = {One common method to fix fractures of the human hand after an accident is an osteosynthesis with Kirschner wires (K-wires) to stabilize the bone fragments. The insertion of K-wires is a delicate minimally invasive surgery, because surgeons operate almost without a sight. Since realistic training methods are time consuming, costly and insufficient, a virtual-reality (VR) based training system for the placement of K-wires was developed. As part of this, the current work deals with the real-time bone drilling simulation using a haptic force-feedback device. To simulate the drilling, we introduce a virtual fixture based force-feedback drilling approach. By decomposition of the drilling task into individual phases, each phase can be handled individually to perfectly control the drilling procedure. We report about the related finite state machine (FSM), describe the haptic feedback of each state and explain, how to avoid jerking of the haptic force-feedback during state transition. The usage of the virtual fixture approach results in a good haptic performance and a stable drilling behavior. This was confirmed by 26 expert surgeons, who evaluated the virtual drilling on the simulator and rated it as very realistic. To make the system even more convincing, we determined real drilling feed rates through experimental pig bone drilling and transferred them to our system. Due to a constant simulation thread we can guarantee a precise drilling motion. Virtual fixtures based force-feedback calculation is able to simulate force-feedback assisted bone drilling with high quality and, thus, will have a great potential in developing medical applications.}, subject = {Handchirurgie}, language = {en} } @article{RueckertRueckertPalm, author = {R{\"u}ckert, Tobias and R{\"u}ckert, Daniel and Palm, Christoph}, title = {Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art}, series = {Computers in Biology and Medicine}, volume = {169}, journal = {Computers in Biology and Medicine}, publisher = {Elsevier}, address = {Amsterdam}, doi = {10.1016/j.compbiomed.2024.107929}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-69830}, pages = {24}, abstract = {In the field of computer- and robot-assisted minimally invasive surgery, enormous progress has been made in recent years based on the recognition of surgical instruments in endoscopic images and videos. In particular, the determination of the position and type of instruments is of great interest. Current work involves both spatial and temporal information, with the idea that predicting the movement of surgical tools over time may improve the quality of the final segmentations. The provision of publicly available datasets has recently encouraged the development of new methods, mainly based on deep learning. In this review, we identify and characterize datasets used for method development and evaluation and quantify their frequency of use in the literature. We further present an overview of the current state of research regarding the segmentation and tracking of minimally invasive surgical instruments in endoscopic images and videos. The paper focuses on methods that work purely visually, without markers of any kind attached to the instruments, considering both single-frame semantic and instance segmentation approaches, as well as those that incorporate temporal information. The publications analyzed were identified through the platforms Google Scholar, Web of Science, and PubMed. The search terms used were "instrument segmentation", "instrument tracking", "surgical tool segmentation", and "surgical tool tracking", resulting in a total of 741 articles published between 01/2015 and 07/2023, of which 123 were included using systematic selection criteria. A discussion of the reviewed literature is provided, highlighting existing shortcomings and emphasizing the available potential for future developments.}, subject = {Deep Learning}, language = {en} } @inproceedings{HoengWiedererEderetal., author = {H{\"o}ng, Simon K. and Wiederer, Jonas and Eder, Friedrich and Obergriesser, Mathias and Linner, Thomas}, title = {Towards AI-enhanced facade planning : integrating human expertise with machine learning-driven parametric modeling}, series = {EC³ \& CIB W78 : 2025 European Conference on Computing in Construction \& 42nd CIB W78 IT in Construction Conference}, volume = {6}, booktitle = {EC³ \& CIB W78 : 2025 European Conference on Computing in Construction \& 42nd CIB W78 IT in Construction Conference}, publisher = {European Council for Computing in Construction}, isbn = {978-9-083451-31-2}, issn = {2684-1150}, doi = {10.35490/EC3.2025.320}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-84862}, pages = {192 -- 199}, abstract = {Planning modern facade systems is complex, requiring optimization across multiple domains.This paper proposes an AI-enhanced workflow for facade planning, harnessing computer vision and human input via a Large Language Model.A generative AI system then guides a parametric model to produce 3D facade designs. Automated checks provide feedback to a Reinforcement Learning system, to iteratively determine optimal solutions.These solutions are verified and finalized by human expertise, ensuring improved outcomes with reduce planning time and effort.The approach illustrates how combining advanced AI methods with human expertise can address the multifactorial challenges of facade design within current industry practices.}, language = {en} } @article{MaerklRueckertRauberetal., author = {Maerkl, Raphaela and Rueckert, Tobias and Rauber, David and Gutbrod, Max and Weber Nunes, Danilo and Palm, Christoph}, title = {Enhancing generalization in zero-shot multi-label endoscopic instrument classification}, series = {International Journal of Computer Assisted Radiology and Surgery}, volume = {20}, journal = {International Journal of Computer Assisted Radiology and Surgery}, publisher = {Springer Nature}, doi = {10.1007/s11548-025-03439-5}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-85674}, pages = {1577 -- 1587}, abstract = {Purpose Recognizing previously unseen classes with neural networks is a significant challenge due to their limited generalization capabilities. This issue is particularly critical in safety-critical domains such as medical applications, where accurate classification is essential for reliability and patient safety. Zero-shot learning methods address this challenge by utilizing additional semantic data, with their performance relying heavily on the quality of the generated embeddings. Methods This work investigates the use of full descriptive sentences, generated by a Sentence-BERT model, as class representations, compared to simpler category-based word embeddings derived from a BERT model. Additionally, the impact of z-score normalization as a post-processing step on these embeddings is explored. The proposed approach is evaluated on a multi-label generalized zero-shot learning task, focusing on the recognition of surgical instruments in endoscopic images from minimally invasive cholecystectomies. Results The results demonstrate that combining sentence embeddings and z-score normalization significantly improves model performance. For unseen classes, the AUROC improves from 43.9\% to 64.9\%, and the multi-label accuracy from 26.1\% to 79.5\%. Overall performance measured across both seen and unseen classes improves from 49.3\% to 64.9\% in AUROC and from 37.3\% to 65.1\% in multi-label accuracy, highlighting the effectiveness of our approach. Conclusion These findings demonstrate that sentence embeddings and z-score normalization can substantially enhance the generalization performance of zero-shot learning models. However, as the study is based on a single dataset, future work should validate the method across diverse datasets and application domains to establish its robustness and broader applicability.}, language = {en} } @article{EsperSchultheissGradetal., author = {Esper, Lukas and Schultheiss, Ulrich and Grad, Marius and Noster, Ulf and Bund, Andreas}, title = {Application of the Hull Cell for Identifying Electropolishing Parameters to Adjust Surface Morphology in Additive Manufacturing}, series = {ECS Advances}, volume = {4}, journal = {ECS Advances}, number = {4}, publisher = {The Electrochemical Society}, issn = {2754-2734}, doi = {10.1149/2754-2734/ae184f}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-86295}, pages = {9}, abstract = {Additively processed materials are increasingly used to manufacture customized parts, e.g. medical implants. Implant surfaces often require a smooth finish, which can be achieved by post-processing and well-defined process parameters. In this study, the effects of electropolishing of metal parts produced by laser powder bed fusion are investigated using Hull cell experiments and a three-electrode setup. Current density voltage curves were measured with the three-electrode setup to identify the regimes for electropolishing. Subsequently different constant-currents were applied and Hull cell experiments were conducted. The surface roughness (Sz, Sa) and the mass removal were analysed. Surface morphologies were assessed using laser scanning and scanning electron microscopy. A reduction of the initial surface roughness of more than 90\% to Sa \< 0.3 μm has been achieved. Considering the passed electrical charge during electropolishing, results from Hull cell experiments are systematically correlated with current-controlled electropolishing. This approach enables the precise tailoring of polishing parameters to achieve surfaces with defined roughness. Furthermore, the study demonstrates the suitability of Hull cells in determining electropolishing parameters for additive materials and highlights their contribution to post-processing in additive manufacturing.}, language = {en} } @article{GreinerLauerSchedeletal., author = {Greiner, Nina and Lauer, Norina and Schedel, Valentin and Pfingsten, Andrea}, title = {Group rehabilitation for adults with acquired neurological disorders: A systematic review of mono- and interdisciplinary interventions in physical and speech-language therapy}, series = {PM\&R}, journal = {PM\&R}, publisher = {Wiley}, doi = {10.1002/pmrj.70006}, pages = {17}, abstract = {Background: Group treatments and interdisciplinary collaboration are recommended in evidence-based guidelines for neurorehabilitation, including physical and speech-language therapy. Evidence suggests that activating overlapping neural networks for upper extremity motor control and speechlanguage processing produces synergistic effects during therapy. This systematic review aims to overview and appraise the efficacy of group treatments in traditional rehabilitation and telerehabilitation. In addition to summarizing evidence on monodisciplinary approaches in physical and speech-language therapy, it seeks data on integrative approaches involving one or both disciplines to inform further interdisciplinary collaboration. Methods: The review was registered with PROSPERO (CRD42021288012) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Systematic searches were conducted in PubMed, CINAHL, and the Cochrane Library. Two reviewers independently screened studies, extracted data, and assessed quality using AMSTAR 2, the Physiotherapy Evidence Database (PEDro) scale, or the Joanna Briggs Institute (JBI) Checklist, as appropriate. The evidence was summarized in a systematic narrative synthesis and its certainty rated based on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Results: A total of 29 studies were included: 16 on speech-language therapy (861 participants) and 13 on physical therapy (1757 participants). No studies addressed interdisciplinary group interventions, and only two evaluated group telerehabilitation. Outcome domains and measures varied across studies and the certainty of evidence was predominantly low. However, moderate-certainty evidence supports that group speech-language therapy improves quality of life, communication, and language in stroke survivors, especially when interventions emphasize verbal production in communicative settings with multimodal materials and cueing. In physical therapy, circuit class training may be more effective than other group approaches for enhancing quality of life and mobility. Conclusion: Group treatments in neurorehabilitation show some benefits, but further research is needed - especially regarding interdisciplinary approaches and telerehabilitation.}, subject = {Gruppentherapie}, language = {en} } @article{BarthelSuessDendorfer, author = {Barthel, Mareike and S{\"u}ß, Franz and Dendorfer, Sebastian}, title = {Application of a transformer encoder for the prediction of intra-abdominal pressure}, series = {Computer Methods in Biomechanics and Biomedical Engineering}, journal = {Computer Methods in Biomechanics and Biomedical Engineering}, publisher = {Taylor \& Francis}, doi = {10.1080/10255842.2025.2586143}, pages = {11}, abstract = {Intra-abdominal pressure is a significant physiological parameter influencing spinal stability and pelvic floor health. This study investigates the potential of a transformer encoder model to predict IAP using motion capture data and musculoskeletal modeling. Data from 211 subjects performing walking, fast walking, and running were used to train a transformer encoder. The model showed promising results with an overall Mean Absolute Percentage Error of 13.5\% and a Pearson correlation coefficient of 0.85. Predictions for fast walking and running proved to be more challenging compared to walking, which was attributed to the greater variability and complexity of faster movements.}, language = {en} } @article{CurrleHaugWeber, author = {Currle, Edda and Haug, Sonja and Weber, Karsten}, title = {Akzeptanz des Einsatzes von K{\"u}nstlicher Intelligenz im Anamneseprozess: Ergebnisse einer Bev{\"o}lkerungsbefragung in Deutschland}, series = {Zeitschrift f{\"u}r Evidenz, Fortbildung und Qualit{\"a}t im Gesundheitswesen}, volume = {198-199}, journal = {Zeitschrift f{\"u}r Evidenz, Fortbildung und Qualit{\"a}t im Gesundheitswesen}, publisher = {Elsevier}, doi = {10.1016/j.zefq.2025.10.003}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-86715}, pages = {9 -- 17}, abstract = {Hintergrund und Zielsetzung Zunehmend werden digitale Anamneseverfahren, wie z. B. Chatbots, entwickelt und evaluiert, sind jedoch in Arztpraxen in Deutschland noch nicht fl{\"a}chendeckend implementiert. Ziel dieser Arbeit ist die Erhebung der Akzeptanz der Bev{\"o}lkerung in Deutschland gegen{\"u}ber KI-gest{\"u}tzten Verfahren im Anamneseprozess, durch die es m{\"o}glich wird, R{\"u}ckschl{\"u}sse auf die Nutzung der Verfahren und ihre Eignung als Bestandteil von Digitalisierungsstrategien der Praxen zu ziehen. Methode Die Studie basiert auf einer Onlinebefragung der Bev{\"o}lkerung in Deutschland (Feldphase 18.-24.11.2024, n = 1.000). Zur{\"u}ckgehend auf die „Unified Theory of Acceptance and Use of Technology" (UTAUT) wurden drei zentrale Hypothesen zur Nutzung von K{\"u}nstlicher Intelligenz (KI) im Anamneseprozess aufgestellt und mit linearen Regressionsmodellen getestet. Ergebnisse Die Akzeptanz f{\"u}r die Nutzung von KI-gest{\"u}tzten Systemen f{\"a}llt in beiden untersuchten Szenarien, der Nutzung eines Chatbots zu Hause und der Nutzung eines Chatbots in einer Arztpraxis, hoch aus. Dabei best{\"a}tigen sich die erwarteten Zusammenh{\"a}nge von Leistungserwartung, Aufwandserwartung und erwartetem Sozialem Einfluss mit der Verhaltensabsicht, einen Chatbot in der Arztpraxis oder vor dem Besuch einer Arztpraxis zu nutzen. Die Einfl{\"u}sse von Alter, Geschlecht oder Erfahrung mit der Technologie zeigen jedoch nicht die vermuteten Zusammenh{\"a}nge. Diskussion und Schlussfolgerung Die Praktikabilit{\"a}t ist von entscheidender Bedeutung f{\"u}r eine positive Einstellung gegen{\"u}ber der Nutzung. Dabei zeigt sich kein Unterschied zwischen den Geschlechtern. Bei der Implementierung von Chatbots im Anamneseprozess sollten die Aspekte Praktikabilit{\"a}t, Datenschutz und Datensicherheit eine wesentliche Rolle spielen. Angesichts der Tatsache, dass ein großer Teil der {\"a}lteren Bev{\"o}lkerung in Deutschland nach wie vor {\"u}ber begrenzte Erfahrung mit digitalen Technologien verf{\"u}gt, ist Gebrauchstauglichkeit f{\"u}r diese Bev{\"o}lkerungsgruppe sowie f{\"u}r Menschen mit Beeintr{\"a}chtigungen von hoher Relevanz.}, language = {de} } @article{WeihererEigenbergerEggeretal., author = {Weiherer, Maximilian and Eigenberger, Andreas and Egger, Bernhard and Br{\´e}bant, Vanessa and Prantl, Lukas and Palm, Christoph}, title = {Learning the shape of female breasts: an open-access 3D statistical shape model of the female breast built from 110 breast scans}, series = {The Visual Computer}, volume = {39}, journal = {The Visual Computer}, number = {4}, publisher = {Springer Nature}, doi = {10.1007/s00371-022-02431-3}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-30506}, pages = {1597 -- 1616}, abstract = {We present the Regensburg Breast Shape Model (RBSM)—a 3D statistical shape model of the female breast built from 110 breast scans acquired in a standing position, and the first publicly available. Together with the model, a fully automated, pairwise surface registration pipeline used to establish dense correspondence among 3D breast scans is introduced. Our method is computationally efficient and requires only four landmarks to guide the registration process. A major challenge when modeling female breasts from surface-only 3D breast scans is the non-separability of breast and thorax. In order to weaken the strong coupling between breast and surrounding areas, we propose to minimize the variance outside the breast region as much as possible. To achieve this goal, a novel concept called breast probability masks (BPMs) is introduced. A BPM assigns probabilities to each point of a 3D breast scan, telling how likely it is that a particular point belongs to the breast area. During registration, we use BPMs to align the template to the target as accurately as possible inside the breast region and only roughly outside. This simple yet effective strategy significantly reduces the unwanted variance outside the breast region, leading to better statistical shape models in which breast shapes are quite well decoupled from the thorax. The RBSM is thus able to produce a variety of different breast shapes as independently as possible from the shape of the thorax. Our systematic experimental evaluation reveals a generalization ability of 0.17 mm and a specificity of 2.8 mm. To underline the expressiveness of the proposed model, we finally demonstrate in two showcase applications how the RBSM can be used for surgical outcome simulation and the prediction of a missing breast from the remaining one. Our model is available at https://www.rbsm.re-mic.de/.}, language = {en} } @article{BrebantWeihererNoisseretal., author = {Br{\´e}bant, Vanessa and Weiherer, Maximilian and Noisser, Vivien and Seitz, Stephan and Prantl, Lukas and Eigenberger, Andreas}, title = {Implants Versus Lipograft: Analysis of Long-Term Results Following Congenital Breast Asymmetry Correction}, series = {Aesthetic Plastic Surgery}, volume = {46}, journal = {Aesthetic Plastic Surgery}, publisher = {Springer Nature}, doi = {10.1007/s00266-022-02843-5}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-32404}, pages = {2228 -- 2236}, abstract = {Aims Congenital breast asymmetry represents a particular challenge to the classic techniques of plastic surgery given the young age of patients at presentation. This study reviews and compares the long-term results of traditional breast augmentation using silicone implants and the more innovative technique of lipografting. Methods To achieve this, we not only captured subjective parameters such as satisfaction with outcome and symmetry, but also objective parameters including breast vol-ume and anthropometric measurements. The objective examination was performed manually and by using the Vectra H2 photogrammetry scanning system. Results Differences between patients undergoing either implant augmentation or lipograft were revealed not to be significant with respect to patient satisfaction with surgical outcome (p= 0.55) and symmetry (p= 0.69). Furthermore, a breast symmetry of 93 \% was reported in both groups. Likewise, no statistically significant volume difference between the left and right breasts was observed in both groups (p\0.41). However, lipograft patients needed on average 2.9 procedures to achieve the desired result, compared with 1.3 for implant augmentation. In contrast, patients treated with implant augmentation may require anumber of implant changes during their lifetime. Conclusion Both methods may be considered for patients presenting with congenital breast asymmetry.}, language = {en} } @article{MaierWeihererHuberetal., author = {Maier, Johannes and Weiherer, Maximilian and Huber, Michaela and Palm, Christoph}, title = {Imitating human soft tissue on basis of a dual-material 3D print using a support-filled metamaterial to provide bimanual haptic for a hand surgery training system}, series = {Quantitative Imaging in Medicine and Surgery}, volume = {9}, journal = {Quantitative Imaging in Medicine and Surgery}, number = {1}, publisher = {AME Publishing Company}, doi = {10.21037/qims.2018.09.17}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-979}, pages = {30 -- 42}, abstract = {Background: Currently, it is common practice to use three-dimensional (3D) printers not only for rapid prototyping in the industry, but also in the medical area to create medical applications for training inexperienced surgeons. In a clinical training simulator for minimally invasive bone drilling to fix hand fractures with Kirschner-wires (K-wires), a 3D-printed hand phantom must not only be geometrically but also haptically correct. Due to a limited view during an operation, surgeons need to perfectly localize underlying risk structures only by feeling of specific bony protrusions of the human hand. Methods: The goal of this experiment is to imitate human soft tissue with its haptic and elasticity for a realistic hand phantom fabrication, using only a dual-material 3D printer and support-material-filled metamaterial between skin and bone. We present our workflow to generate lattice structures between hard bone and soft skin with iterative cube edge (CE) or cube face (CF) unit cells. Cuboid and finger shaped sample prints with and without inner hard bone in different lattice thickness are constructed and 3D printed. Results: The most elastic available rubber-like material is too firm to imitate soft tissue. By reducing the amount of rubber in the inner volume through support material (SUP), objects become significantly softer. Without metamaterial, after disintegration, the SUP can be shifted through the volume and thus the body loses its original shape. Although the CE design increases the elasticity, it cannot restore the fabric form. In contrast to CE, the CF design increases not only the elasticity but also guarantees a local limitation of the SUP. Therefore, the body retains its shape and internal bones remain in its intended place. Various unit cell sizes, lattice thickening and skin thickness regulate the rubber material and SUP ratio. Test prints with higher SUP and lower rubber material percentage appear softer and vice versa. This was confirmed by an expert surgeon evaluation. Subjects adjudged pure rubber-like material as too firm and samples only filled with SUP or lattice structure in CE design as not suitable for imitating tissue. 3D-printed finger samples in CF design were rated as realistic compared to the haptic of human tissue with a good palpable bone structure. Conclusions: We developed a new dual-material 3D print technique to imitate soft tissue of the human hand with its haptic properties. Blowy SUP is trapped within a lattice structure to soften rubber-like 3D print material, which makes it possible to reproduce a realistic replica of human hand soft tissue.}, subject = {Handchirurgie}, language = {en} } @article{MaierWeihererHuberetal., author = {Maier, Johannes and Weiherer, Maximilian and Huber, Michaela and Palm, Christoph}, title = {Optically tracked and 3D printed haptic phantom hand for surgical training system}, series = {Quantitative Imaging in Medicine and Surgery}, volume = {10}, journal = {Quantitative Imaging in Medicine and Surgery}, number = {02}, publisher = {AME Publishing Company}, address = {Hong Kong, China}, doi = {10.21037/qims.2019.12.03}, pages = {340 -- 455}, abstract = {Background: For surgical fixation of bone fractures of the human hand, so-called Kirschner-wires (K-wires) are drilled through bone fragments. Due to the minimally invasive drilling procedures without a view of risk structures like vessels and nerves, a thorough training of young surgeons is necessary. For the development of a virtual reality (VR) based training system, a three-dimensional (3D) printed phantom hand is required. To ensure an intuitive operation, this phantom hand has to be realistic in both, its position relative to the driller as well as in its haptic features. The softest 3D printing material available on the market, however, is too hard to imitate human soft tissue. Therefore, a support-material (SUP) filled metamaterial is used to soften the raw material. Realistic haptic features are important to palpate protrusions of the bone to determine the drilling starting point and angle. An optical real-time tracking is used to transfer position and rotation to the training system. Methods: A metamaterial already developed in previous work is further improved by use of a new unit cell. Thus, the amount of SUP within the volume can be increased and the tissue is softened further. In addition, the human anatomy is transferred to the entire hand model. A subcutaneous fat layer and penetration of air through pores into the volume simulate shiftability of skin layers. For optical tracking, a rotationally symmetrical marker attached to the phantom hand with corresponding reference marker is developed. In order to ensure trouble-free position transmission, various types of marker point applications are tested. Results: Several cuboid and forearm sample prints lead to a final 30 centimeter long hand model. The whole haptic phantom could be printed faultless within about 17 hours. The metamaterial consisting of the new unit cell results in an increased SUP share of 4.32\%. Validated by an expert surgeon study, this allows in combination with a displacement of the uppermost skin layer a good palpability of the bones. Tracking of the hand marker in dodecahedron design works trouble-free in conjunction with a reference marker attached to the worktop of the training system. Conclusions: In this work, an optically tracked and haptically correct phantom hand was developed using dual-material 3D printing, which can be easily integrated into a surgical training system.}, subject = {Handchirurgie}, language = {en} } @article{EbigboMendelProbstetal., author = {Ebigbo, Alanna and Mendel, Robert and Probst, Andreas and Manzeneder, Johannes and Souza Jr., Luis Antonio de and Papa, Jo{\~a}o Paulo and Palm, Christoph and Messmann, Helmut}, title = {Computer-aided diagnosis using deep learning in the evaluation of early oesophageal adenocarcinoma}, series = {GuT}, volume = {68}, journal = {GuT}, number = {7}, publisher = {British Society of Gastroenterology}, doi = {10.1136/gutjnl-2018-317573}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-68}, pages = {1143 -- 1145}, abstract = {Computer-aided diagnosis using deep learning (CAD-DL) may be an instrument to improve endoscopic assessment of Barrett's oesophagus (BE) and early oesophageal adenocarcinoma (EAC). Based on still images from two databases, the diagnosis of EAC by CAD-DL reached sensitivities/specificities of 97\%/88\% (Augsburg data) and 92\%/100\% (Medical Image Computing and Computer-Assisted Intervention [MICCAI] data) for white light (WL) images and 94\%/80\% for narrow band images (NBI) (Augsburg data), respectively. Tumour margins delineated by experts into images were detected satisfactorily with a Dice coefficient (D) of 0.72. This could be a first step towards CAD-DL for BE assessment. If developed further, it could become a useful adjunctive tool for patient management.}, subject = {Speiser{\"o}hrenkrebs}, language = {en} }