A5067626715- Cell Image Analysis Techniques
- 3D Printing in Biomedical Research
- Image Processing Techniques and Applications
- Cancer Cells and Metastasis
- AI in cancer detection
- Cellular Mechanics and Interactions
- Additive Manufacturing and 3D Printing Technologies
- Generative Adversarial Networks and Image Synthesis
- Advanced Fluorescence Microscopy Techniques
- Viral Infectious Diseases and Gene Expression in Insects
- Water Quality Monitoring Technologies
- Digital Imaging for Blood Diseases
- 3D Shape Modeling and Analysis
- Mathematical Biology Tumor Growth
- Advanced Vision and Imaging
- Computer Graphics and Visualization Techniques
- Bone Metabolism and Diseases
- Advanced Image Processing Techniques
- Fish Ecology and Management Studies
- Image and Object Detection Techniques
- Pluripotent Stem Cells Research
- Nerve injury and regeneration
- Insect Pheromone Research and Control
- Microfluidic and Bio-sensing Technologies
- Cancer Research and Treatments
Karlsruhe Institute of Technology
2022-2025
Mannheim University of Applied Sciences
2020-2024
Three-dimensional cell cultures, such as spheroids and organoids, serve increasingly important models in fundamental applied research start to be used for drug screening purposes. Optical tissue clearing procedures are employed enhance visualization of fluorescence-stained organs, tissues, three-dimensional cultures. To get a more systematic overview about the effects applicability optical on we compared six different / embedding protocols seven types spheroid- chip-based cultures...
Abstract Biomedical research increasingly relies on three-dimensional (3D) cell culture models and artificial-intelligence-based analysis can potentially facilitate a detailed accurate feature extraction single-cell level. However, this requires for precise segmentation of 3D datasets, which in turn demands high-quality ground truth training. Manual annotation, the gold standard data, is too time-consuming thus not feasible generation large training datasets. To address this, we present...
Motoneurons, skeletal muscle fibers, and Schwann cells form synapses, termed neuromuscular junctions (NMJs). These control voluntary body movement are affected in numerous diseases. Therefore, a variety of NMJ vitro models have been explored to enable mechanistic pharmacological studies. So far, selective integration these has hampered, due technical limitations. Here we present robust protocols for derivation from human induced pluripotent stem (hiPSC) their coculture with hiPSC-derived...
Most tumors consume large amounts of glucose. Concepts to explain the mechanisms that mediate achievement this metabolic need have proposed a switch tumor mass aerobic glycolysis. Depending on whether primarily or stroma cells undergo such commutation, terms ‘Warburg effect’ ‘reverse Warburg were coined describe underlying biological phenomena. However, current in vitro systems relying 2-D culture, single cell-type spheroids, basal-membrane extract (BME/Matrigel)-containing 3-D structures do...
The analysis of 3D microscopic cell culture images plays a vital role in the development new therapeutics. While cultures offer greater similarity to human organism than adherent cultures, they introduce challenges for automatic evaluation, like increased heterogeneity. Deep learning algorithms are able outperform conventional methods such conditions but require large amount training data. Due data size and complexity, manual annotation generate datasets is nearly impossible task. We...
Abstract Spheroids have become principal three-dimensional biological models to study cancer, developmental processes, and drug efficacy. For spheroid generation, ultra-low attachment plates are noteworthy due their simplicity, compatibility with automation, experimental commercial accessibility. Nonetheless, it is unknown whether what degree the plate type impacts formation biology. This employed automated brightfield microscopy systematically compare size eccentricity of spheroids formed...
3D cell culture models replicate tissue complexity and aim to study cellular interactions responses in a more physiologically relevant environment compared traditional 2D cultures. However, the spherical structure of these makes it difficult extract meaningful data, necessitating advanced techniques for proper analysis. In silico simulations enhance research by predicting behaviors therapeutic responses, providing powerful tool complement experimental approaches. Despite their potential,...
Abstract U-Net is the go-to approach for biomedical segmentation applications. However, it not designed to segment overlapping objects, a challenge Mask R-CNN has shown have great potential in. Yet, receives little attention in biomedicine. Hence, we evaluate both approaches on publicly available dataset. We find that RCNN outperforms segmenting cells and achieves comparable performance if they do intersect. Our study provides valuable decision support practitioners selecting an appropriate...
Abstract 3D cell culture models replicate tissue complexity, aiming to study cellular interactions and responses in a more physiologically relevant environment compared traditional 2D cultures. However, the spherical structure of these makes it difficult extract meaningful data, necessitating advanced techniques for proper analysis. In silico simulations enhance research by predicting behaviors therapeutic responses, providing powerful tool complement experimental approaches. Despite their...
Spheroids have become principal three-dimensional models to study cancer, developmental processes, and drug efficacy. Single-cell analysis techniques emerged as ideal tools gauge the complexity of cellular responses in these models. However, single-cell quantitative assessment based on 3D-microscopic data subcellular distribution fluorescence markers, such nuclear/cytoplasm ratio transcription factors, has largely remained elusive. For spheroid generation, ultra-low attachment plates are...
Biomedical research increasingly relies on 3D cell culture models and AI-based analysis can potentially facilitate a detailed accurate feature extraction single-cell level. However, this requires for precise segmentation of datasets, which in turn demands high-quality ground truth training. Manual annotation, the gold standard data, is too time-consuming thus not feasible generation large training datasets. To address this, we present novel framework generating integrates biophysical...
Abstract Background The growth and drug response of tumors are influenced by their stromal composition, both in vivo 3D-cell culture models. Cell-type inherent features as well mutual relationships between the different cell types a tumor might affect susceptibility whole and/or its populations. However, lack single-cell procedures with sufficient detail has hampered automated observation cell-type-specific effects three-dimensional stroma-tumor co-cultures. Methods Here, we developed...
Abstract The analysis of microscopic images from cell cultures plays an important role in the development drugs. segmentation such is a basic step to extract viable information on which further evaluation steps are build. Classical image processing pipelines often fail under heterogeneous conditions. In recent years deep neuronal networks gained attention due their great potentials segmentation. One main pitfall learning seen amount labeled data required for training models. Especially 3D...
Abstract Supervised Neural Networks are used for segmentation in many biological and biomedical applications. To omit the time-consuming tiring process of manual labeling, unsupervised Generative Adversarial (GANs) can be to synthesize labeled data. However, training GANs requires extensive computation is often unstable. Due lack established stopping criteria, usually trained multiple times a heuristically fixed number epochs. Early epoch selection lead better synthetic datasets resulting...
Bone sialoprotein (BSP) has become a target in breast cancer research as it is associated with tumor progression and metastasis. The mechanisms underlying the regulation of BSP expression have been largely elusive. Given that involved homing cells bone metastatic niches, we addressed regulatory effects proteolytic cleavage extracellular matrix components on distribution cell culture models. Therefore, MDA-MB-231 human were kept 2D 3D spheroid cultures exposed to basement membrane extract...
Behavioral analysis of moving animals relies on a faithful recording and track to extract relevant parameters movement. To study group behavior social interactions, often simultaneous analyses individuals are required. detect for example identify the leader as opposed followers, one needs an error-free segmentation individual tracks throughout time. While automated tracking algorithms exist that quick easy use, inevitable errors will occur during tracking. solve this problem, we introduce...
Abstract 3D cell culture models are important tools for the development and testing of new therapeutics. In combination with immunoassays confocal microscopy, crucial information like morphological or metabolic changes can be examined during drug testing. However, a common limitation immunostainings is number dyes that imaged simultaneously, as overlaps in spectral profiles different may result cross talk. We therefore present deep learning method, able to predict fluorescent stainings...
Deep learning models for image segmentation achieve high-quality results, but need large amounts of training data. Training data is primarily annotated manually, which time-consuming and often not feasible large-scale 2D 3D images. Manual annotation can be reduced using synthetic generated by generative adversarial networks that perform unpaired image-to-image translation. As now, images to processed patch-wise during inference, resulting in local artifacts border regions after merging the...