bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mask R-CNN Outperforms U-Net in Instance Segmentation for Overlapping Cells
Authors: Rettenberger Luca , Rieken Münke Friedrich , Bruch Roman , Reischl Markus 
Published: September 2023

Abstract
U-Net is the go-to approach for biomedical segmentation applications. However, it is not designed to segment overlapping objects, a challenge Mask R-CNN has shown to have great potential in. Yet, Mask R-CNN receives little attention in biomedicine. Hence, we evaluate both approaches on a publicly available biomedical dataset. We find that Mask RCNN outperforms U-Net in segmenting overlapping cells and achieves comparable performance if they do not intersect. Our study provides valuable decision support to practitioners in selecting an appropriate method when solving instance segmentation tasks using deep learning, as well as important insights into enhancing the accuracy of such approaches in biomedical image analysis.
Validation of ergonomic running handgrip elements to improve arm posture of running novices
Authors: Sesselmann Stefan , Turcanu Michael , Fleischmann Christopher , Leher Irina , Schleip Robert , Buhl Sebastian , Schuh Alexander 
Published: September 2023

Abstract
Running is one of the most popular sports worldwide motivating many non-athletic people to start new physical activities. But especially novice runners are at risk to develop injuries as they tend to run with prejudicial posture. Hence, there has been considerable research to identify factors improving running performance. One of these factors is the correct movement of arms as a swinging pendulum during running. Based on this knowledge ergonomically shaped handgrip elements were designed to improve the posture of the shoulder-arm complex during running. The main objective of this study was the validation of the actual effectiveness on shoulder-arm posture of these handgrips. In this sense 25 adult, healthy persons without running experience were examined by motion capture analysis during running on a treadmill with and without the use of the handgrips. The focus of movement analysis was on changes of hand supination, shoulder abduction and shoulder rotation. Flexion of elbows and shoulders were not expected to change and thus, were investigated as an internal control. Significant changes were found in sense of a reduction of forearm pronation, shoulder abduction, and internal rotation of the shoulder, resulting in improved posture during running. At the same time, no significant changes were found in elbow flexion and shoulder flexion. Future studies are needed to investigate the effects of the detected improvement of arm posture on other important running parameters, such as trunk stability, movement of lower limbs, running economy, and risk of injury. These studies should also compare effects in competitive athletes, recreational runners, and novice runners.
Single-photon avalanche diode (SPAD) array detector for high-throughput fluorescence lifetime flow cytometry
Authors: Rottmann Jonas , Schierbaum Nicolas , Netaev Alexander , Ligges Manuel , Seidl Karsten 
Published: September 2023

Abstract
Time-domain measurement of the fluorescence lifetime in flow cytometry offers a complementary method to traditional flow cytometry, especially for the analysis of cells and biomolecules. Short measurement times due to high throughputs (cells/s) make a suited detector mandatory for a sufficient detection of the fluorescence signal and therefore the application of this method. We summarize the requirements for a suited detector for time resolved flow cytometry (TRFC) and present a new developed SPAD array detector with 100 pixels and 340 ns time between measurement windows, allowing a high-throughput of up to 60,000 cells/s. The functionality of the detector is shown with the measurement of a 22.2 ns laser pulse, making it applicable for an improved TRFC.
Novel airflow ring for the reduction of germ load in a surgical field
Authors: Scherrieble Andreas , Haab Elena , Held-Föhn Evi , Linti Carsten , Baumgartner Tobias , Wandres Claus G. , Doser Michael , Gresser Götz T. 
Published: September 2023

Abstract
Hospital-acquired infections occur through microbial contamination of the surgical wound and can lead to severe complications. A significant transmission path is the aerogenic transmission, where pathogens stick to floating particles like skin scales or to air moisture. A novel porous airflow ring which is placed around the surgical field aims to overcome this by applying sterile air directly at the operation wound. The ring is provided with an air tight coating at the outer side and allows for fixation on the skin by an adhesive coating at the lower side. To evaluate its performance the airflow ring was placed in an atmosphere with nebulized suspension of Staphylococcus arlettae of a concentration of 5.0 x 10^5 CFU/ml resp. 5.0 x 10^6 CFU/ml within a box. The formation of bacterial colonies (CFU) on contact plates placed within the airflow ring was subsequently determined by visual counting after incubating at 37 °C for one day. CFU counts of the ventilated and the unventilated situation were compared. With the smaller inoculum, the introduction of bacteria into the inner site of the ring was completely prevented, whereas the contact plate of the unventilated ring resulted in 77 to 427 colonies in different trials. With the higher inoculum, the bacteria ingress was very strongly reduced by 99.7% respectively 99.9%. In conclusion the airflow ring shows a strong shielding effect for germs adhered to fog-sized water droplets. To clearly demonstrate the effect, the number of bacteria was greatly increased compared to reality in this setup. It was shown that it can withstand even conditions significantly worse than those encountered in an operating theatre. In order to demonstrate the effect in vivo, clinical trials have to be conducted to confirm the laboratory results.
Fabrication of flexible intracranial aneurysm models using stereolithography 3D printing
Authors: Stahl Janneck , Kassem Leheng , Behme Daniel , Klebingat Stefan , Saalfeld Sylvia , Berg Philipp 
Published: September 2023

Abstract
The use of 3D printing technology for medical applications is becoming increasingly popular. Recent stereolithography (SLA)-based printing methods allow the generation of complex structures with a high surface quality. This is particularly useful for applications in the neurovascular field, where sophisticated structures are involved. In this study patient-specific intracranial aneurysm models are extracted based on medical image data und printed as thin-walled vascular phantom models. For this purpose, two commercially available 3D printers are used to print flexible vascular models with three different silicone-like elastic resins (Ultracur3D FL 300, Prusament Flex80 and Formlabs Elastic 50A) of various Shore hardness. Three aneurysm models of different size and complexity are chosen. To evaluate the geometric accuracy of the flexible models, angiographic measurements are performed for an exemplary case and morphological parameters are extracted from the generated 3D models. The printed results demonstrate a successful generation of hollow aneurysm phantoms. There are dependencies regarding the print quality from the model to platform positioning for two materials. The quantitative geometric accuracy analysis shows notable differences between the materials. The extracted morphological parameter values for all materials show a mean decrease compared to the original reference model of aneurysm volume (4.5 %) and maximum diameter (1.0 %) as well as an increase of ostium area (6.0 %) and maximum height (4.9 %). However, Formlabs Elastic 50A in particular exhibits just slight reductions with respect to the reference model, with a mean decrease for all parameters of 5.7 % as well as no dependence on printing position and resulting artifacts. The study investigates the feasibility of using SLA-based 3D printing to generate realistic flexible aneurysm phantoms. In this context, the Formlabs Elastic 50A could be identified as potentially applicable for phantom creation in terms of reproducible quality and geometric validity.
Deep.Neural.Signal.Pre-Processor - Towards Development of AI-enhanced End-to-End BCIs
Authors: Buron Leo , Erbslöh Andreas , Ur-Rehman Zia , Klaes Christian , Seidl Karsten , Schiele Gregor 
Published: September 2023

Abstract
This paper presents a software-based Python framework for developing future AI-enhanced end-to-end Brain-Computer-Interfaces (BCI). This framework contains modules from the emulated analogue front-end and from neural signal pre-processing for invasive neural applications. These modules can be assembled into several pipeline versions for evaluation and benchmarking. The aim of this framework is to accelerate the development of BCIs due to system-wide optimizations in order to set the requirements for hardware development without prior knowledge on the basis of accuracy (recall and precision) and latency. In the next step, the pipeline can be optimised for on-chip and embedded execution.
Development of a test setup for hydrodynamic characterization of hydrocephalus shunts
Authors: Stiehm Michael , Siewert Stefan , Borowski Finja , Großmann Swen , Schmitz Klaus-Peter , Freiman Thomas M. , Strauß Andreas 
Published: September 2023

Abstract
Implantation of a shunt system is the most common neurosurgical procedure for the treatment of hydrocephalus. Hydrodynamic parameters of hydrocephalus shunt systems are valuable variables to address patients' needs. In this report, we present a test setup to evaluate hydrodynamic parameters of hydrocephalus shunt systems. The test setup was validated using a stainless steel capillary and compared with the analytical solution according to Bernoulli's equation. It was demonstrated that the experimental setup is able to model the pressure in a physiologically relevant range. The measured and averaged flow resistance was 2.96 mmHg/(ml min-1). According to the analytical solution of Bernoulli's equation, the flow resistance is 2.86 mmHg/(ml min-1). Therefore, the measured flow resistance is 3.5% higher than the analytical solution. Moreover, the nonlinear characteristic of the pressure drop at the inlet and outlet of the capillary plays a minor role compared to the friction of the tube flow. As a result, the increase in flow rate with increasing pressure load can be well approximated by a linear function for the low flow rates measured here. The experimental setup presented will be used in the future to characterize commercially available shunt systems under various hydrodynamic conditions.
Discrepancy Between LGE-MRI and Electro-Anatomical Mapping for Regional Detection of Pathological Atrial Substrate
Authors: Goetz Christian , Martínez Díaz Patricia , Sánchez Jorge , Jadidi Amir , Eichenlaub Martin , Dössel Olaf , Loewe Axel 
Published: September 2023

Abstract
Atrial fibrillation (AF) is the most common sustained arrhythmia posing a significant burden to patients and leading to an increased risk of stroke and heart failure. Additional ablation of areas of arrhythmogenic substrate in the atrial body detected by either late gadolinium enhancement magnetic resonance imaging (LGE-MRI) or electroanatomical mapping (EAM) may increase the success rate of restoring and maintaining sinus rhythm compared to the standard treatment procedure of pulmonary vein isolation (PVI). To evaluate if LGE-MRI and EAM identify equivalent substrate as potential ablation targets, we divided the left atrium (LA) into six clinically important regions in ten patients. Then, we computed the correlation between both modalities by analyzing the regional extents of identified pathological tissue. In this regional analysis, we observed no correlation between late gadolinium enhancement (LGE) and low voltage areas (LVA), neither in any region nor with regard to the entire atrial surface (-0.3<r<0.3). Instead, the regional extents identified as pathological tissue varied significantly between both modalities. An increased extent of LVA compared to LGE was observed in the septal wall of the LA (asept.,LVA= 19.63% and asept.,LGE= 3.94%, with = median of the extent of pathological tissue in the corresponding region). In contrast, in the inferior and lateral wall, the extent of LGE was higher than the extent of LVA for most geometries (ainf.,LGE= 27.22% and alat.,LGE= 32.70% compared to ainf.,LVA= 9.21% and alat.,LVA= 6.69%). Since both modalities provided discrepant results regarding the detection of arrhythmogenic substrate using clinically established thresholds, further investigations regarding their constraints need to be performed in order to use these modalities for patient stratification and treatment planning.
Accuracy Evaluation of 3D Pose Estimation with MediaPipe Pose for Physical Exercises
Authors: Dill Sebastian , Rösch Andreas , Rohr Maurice , Güney Gökhan , De Witte Luisa , Schwartz Elias , Hoog Antink Christoph 
Published: September 2023

Abstract
With the recent increase in interest in machine learning and computer vision, camera-based pose estimation has emerged as a promising new technology. One of the most popular libraries for camera-based pose estimation is MediaPipe Pose due to its computational efficiency, ease of use, and the fact that it is open-source. However, little work has been performed to establish how accurate the library is and whether it is suitable for usage in, for example, physical therapy. This paper aims to provide an initial assessment of this. We find that the pose estimation is highly dependent on the camera’s viewing angle as well as the performed exercise. While high accuracy can be achieved under optimal conditions, the accuracy quickly decreases when the conditions are less favourable.
Transmission of Vital Data into the German Electronic Health Record
Authors: Keil Alexander , Brück Rainer , Hahn Kai 
Published: September 2023

Abstract
Patient’s vital data will have an important role in future medicine. Best way to store this data is the patient’s electronic health record (EHR) in a structured form. In Germany, several laws, regulations and standards must be considered to store vital data in the health record, like SGB V, DIGAV and Medical Information Objects. In the near future, it will be possible to upload self-recorded vital data to the German EHR special smartphone apps. It will also be possible to automatically evaluate this data using machine learning.
Deep Semantic Segmentation of Cell Painted Nuclei Images using UNet++
Authors: Palliyil Sreekumar Sreelekshmi , Palanisamy Rohini , Swaminathan Ramakrishnan 
Published: September 2023

Abstract
Fluorescence microscopy based cell painting technique profiles the morphological characteristics of specific cell organelles with high resolution. However, photo toxicity, photo bleaching and advanced instrumentation limits its utility for comprehensively annotating the cell structure. Generating cell painted organelles from simple and least invasive transmitted light microscopy provides a surrogate for clinical applications. In this study, the employability of semantic segmentation model for delineating the nuclei from composite image using UNet++ is investigated. For this, a public dataset consisting of 3456 composite images are considered from Broad Bioimage Benchmark collection. The binary masks of endoplasmic reticulum (ER), nuclei and cytoplasm are generated for pixel wise labelling. The composite images and their labelled dataset are fed to the UNet++ model for segmenting the cell painted nuclei. The performance of the deep semantic network is analysed for 50 epochs and the segmentation results are validated with mean intersection-over-union (IoU). The UNet++model provides an accuracy of 95.8% with a minimum loss of 0.1. Mean IoU of 0.91 is achieved for the prediction of nuclei from the composite images. The obtained results suggest that this study could be employed for predicting the subcellular components from transmitted light microscopy without the use of fluorescent labelling.
Reduction of Uncertainty in Bolus Transit Time Measurement in Quantitative Fluorescence Angiography
Authors: Gao Yang , Weiß Miriam , Nahm Werner 
Published: September 2023

Abstract
During cerebral revascularization surgeries, blood flow values help surgeons to monitor the quality of the procedure, e.g., to avoid cerebral hyperperfusion syndrome due to excessively enhanced perfusion. The state-of-the-art technique is the ultrasonic flow probe that has to be placed around the blood vessel. This causes contact between probe and vessel, which, in the worst case, leads to rupture. The recently developed intraoperative indocyanine green (ICG) Quantitative Fluorescence Angiography (QFA) is an alternative technique that overcomes this risk. However, it has been shown by the developer that the calculated flow has deviations. After determining the bolus transit time as the most sensitive parameter in flow calculation, we propose a new two-step uncertainty reduction method for flow calculation. The first step is to generate more data in each measurement that results in functions of the parameters. Noise can then be reduced in a second step. Two methods for this step are compared. The first method fits the model for each parameter function separately and calculates flow from models, while the second one fits multiple parameter functions together. The latter method is proven to perform best by in silico tests. Besides, this method reduces the deviation of flow comparing to original QFA as expected. Our approach can be generally used in all QFA applications using two-point theory. Further development is possible if number of dimensions of the achieved parameter data are broadened that results in even more data for processing in the second step.
Resolution-based comparative analysis of 4D-phase-contrast magnetic resonance images and hemodynamic simulations of the aortic arch
Authors: Korte J. , Groschopp P. , Berg P. 
Published: September 2023

Abstract
Introduction: In this study, phase-contrast magnetic resonance imaging (PC-MRI) 4D flow data for patients with bicuspid aortic valve (BAV) were analyzed based on the spatial resolution of the images. BAV is a congenital heart defect characterized by the presence of two cusps in the aortic valve, leading to various complications. PC-MRI is a noninvasive imaging technique used to assess the hemodynamics in patients. However, interpretation of PC-MRI data can be challenging due to complex hemodynamics, which makes numerical simulations necessary to complement the results. Methods:Within this study PC-MRI 4D flow data in the aortic arch (AA) were compared with hemodynamic numerical simulations based on the MRI resolution for six patient-specific AAs with BAV. First, the segmentations were reconstructed and divided into three groups based on the resolution. Second, the numerical simulations were performed and resulting hemodynamics compared to PC-MRI results at three time points in the cardiac cycle using velocity and wall shear stress. Results: Results from group 1 (highest resolution) show an overestimation of wall shear stress (WSS) values during peaksystole in the three arteries and along the AA and descending aorta (DAo). Nevertheless, velocity mean values show an overall good agreement. Group 2 shows higher velocity magnitudes in the simulation than in PC-MRI. Within group 3, velocity values differ from the measurements. Conclusion: The study shows that with a low resolution, flow patterns can already be evaluated based on PC-MRI, but to get an insight into the flow quantitatively a higher resolution is necessary.
Quantitative ECG based emotion state recognition using Detrended Fluctuation Analysis
Authors: Anandan Meena , Veluswamy Pandiyarasan , Palanisamy Rohini 
Published: September 2023

Abstract
Wearable emotion recogniton system is essential in identifying mental health disorders by early detection and continuous monitoring of human emotions to provide proper treatment care. Electrocardiogram (ECG) signals can be used for emotion recognition for its noninvasiveness and easy usability. In this study, Detrended Fluctuation Analysis (DFA) and Extreme Gradient Boost (XG Boost) classifier is used to classify the scary and boring emotion from the ECG signals. For this, ECG signal corresponding to these emotions are obtained from public database. The preprocessing is performed by adding the video IDs to the signal and annotating it. This preprocessed signal is subjected to DFA to understand the power-law correlations and similarity property. Further, from the power law correlations, features namely Hurst exponent and DFA intercept are extracted. These features are subjected to XG Boost classifier to differentiate the two emotions. Results shows that the log-log plot of power law correlation is linear in nature which indicates that ECG signals of both the emotions have long range correlations and self-similarity property. The extracted scaling exponent indicates variations between scary and boring with a mean and standard deviation of 0.81±0.13 and 0.68±0.07 respectively. Similarly, DFA intercept provides mean and standard deviation for scary and boring 0.15±0.06 and 0.17±0.07 respectively, showing less variability in the ECG signal. XG Boost classifier gives accuracy of 80.5% for classifying scary and boring emotion. Thus, the proposed approach can be used for wearable emotion recognition system to differentiate scary and boring emotion.
Investigation of the antiadhesive properties of biomimetic titanium nanostructures in fluidic flow
Authors: Kremer Lea , Falk Fabian , Hüschelrath Litsy , Doll Patrick 
Published: September 2023

Abstract
Within this work, the bacterial adhesion on biomimetic titanium nanostructures is investigated in fluidic flow. The motile, gram-negative bacteria strain Escherichia coli was used for the experiments and was incubated on nanostructured titanium, polished titanium and on the wings of the dragonfly Neuorbasis kaupi. After incubation period different flow velocities have been applied and the reduction of adhered bacteria was determined via fluorescence microscopy. Results show that nanostructured titanium surfaces have the ability to reduce the bacterial contamination as it is for the dragon fly wings used in this study. This behavior can also be predicted by analyzing the bearing area of the nanotopography which describes the actual part of the topography which is in contact to the bacteria.
Evaluating thermal properties and activation energy of phthalonitrile using sulfur-containing curing agents
Authors: Lee Joon Hyuk , Jeon Eunkyung , Song Jung-kun , Son Yujin , Choi Jaeho 
Published: September 2023

Abstract
This work used the Kissinger equation to compute the activation energy of phthalonitrile to observe thermal properties. We initiated our investigation by synthesizing phthalonitrile samples, incorporating sulfur-containing curing agents ranging from 2 to 10%. Energy-dispersive X-ray spectroscopy confirmed the success of the curing process. Subsequently, we used thermogravimetric analysis (TGA) to acquire the necessary dataset for input into the Kissinger equation. The TGA results pointed to a direct relationship between the concentration of the curing agent and the thermal stability of the samples. Specifically, a sample treated with a 2% sulfur-containing curing agent demonstrated a moderate thermal stability (Td5%: 527.11°C). However, samples treated with higher concentrations of the curing agent, namely, 5 and 10%, exhibited increased Td5% values of 532.75 and 540.01°C, respectively. The increased thermal degradation-onset temperatures suggest a boost in the cross-linking density and mechanical properties, a result of the increased curing agent concentration. Further substantiating these findings, the Kissinger equation yielded high activation energies of 43.6222, 46.1365, and 67.9515 kcal·mol−1 for the 2, 5, and 10% curing agent dosages, respectively, with R² values ranging from 0.9650 to 0.9701.