A5052870302- Cell Image Analysis Techniques
- Advanced Fluorescence Microscopy Techniques
- AI in cancer detection
- Image Processing Techniques and Applications
- Medical Image Segmentation Techniques
- Digital Imaging for Blood Diseases
- Advanced Neural Network Applications
- COVID-19 diagnosis using AI
- Advanced Polymer Synthesis and Characterization
- Photopolymerization techniques and applications
- Radiomics and Machine Learning in Medical Imaging
- Single-cell and spatial transcriptomics
- Radical Photochemical Reactions
- Advanced Biosensing Techniques and Applications
- Neutrophil, Myeloperoxidase and Oxidative Mechanisms
- Domain Adaptation and Few-Shot Learning
- Advanced Electron Microscopy Techniques and Applications
- Immunotherapy and Immune Responses
- Generative Adversarial Networks and Image Synthesis
- Artificial Intelligence in Healthcare and Education
- Medical Imaging and Analysis
- Neuroinflammation and Neurodegeneration Mechanisms
- Cellular Mechanics and Interactions
- Machine Learning in Healthcare
- Anatomy and Medical Technology
Leibniz Institute for Analytical Sciences - ISAS
2021-2025
Fuzhou University
2022-2024
Xiamen University
2024
Allen Institute for Cell Science
2018-2023
Kirchhoff (Germany)
2023
Tianjin Polytechnic University
2021
University of Notre Dame
2014-2020
Segmentation of 3D images is a fundamental problem in biomedical image analysis. Deep learning (DL) approaches have achieved state-of-the-art segmentation perfor- mance. To exploit the contexts using neural networks, known DL methods, including convolution, 2D convolution on planes orthogonal to slices, and LSTM multiple directions, all suffer incompatibility with highly anisotropic dimensions common images. In this paper, we propose new framework for segmentation, based com- bination fully...
Understanding how a subset of expressed genes dictates cellular phenotype is considerable challenge owing to the large numbers molecules involved, their combinatorics and plethora behaviours that they determine
Abstract A continuing challenge in quantitative cell biology is the accurate and robust 3D segmentation of structures interest from fluorescence microscopy images an automated, reproducible, widely accessible manner for subsequent interpretable data analysis. We describe Allen Cell Structure Segmenter (Segmenter), a Python-based open source toolkit developed cells intracellular microscope images. This brings together classic image iterative deep learning workflows first to generate initial...
Post-injury dysfunction of humoral immunity accounts for infections and poor outcomes in cardiovascular diseases. Among immunoglobulins (Ig), IgA, the most abundant mucosal antibody, is produced by plasma B cells intestinal Peyer's patches (PP) lamina propria. Here we show that patients with stroke myocardial ischemia (MI) had strongly reduced IgA blood levels. This was phenocopied experimental mouse models where decreased fecal were accompanied rapid loss IgA-producing PP Reduced IgG...
Deep learning has been applied successfully to many biomedical image segmentation tasks. However, due the diversity and complexity of data, manual annotation for training common deep models is very timeconsuming labor-intensive, especially because normally only experts can annotate data well. Human are often involved in a long iterative process annotation, as active type schemes. In this paper, we propose representative (RA), new framework reducing effort segmentation. RA uses unsupervised...
Although some cell types may be defined anatomically or by physiological function, a rigorous definition of state remains elusive. Here, we develop quantitative, imaging-based platform for the systematic and automated classification subcellular organization in single cells. We use this to quantify gene expression >30,000 individual human induced pluripotent stem cell-derived cardiomyocytes, producing publicly available dataset that describes population distributions local global sarcomere...
Light-sheet fluorescence microscopy (LSFM) can produce high-resolution tomograms of tissue vasculature with high accuracy. However, data processing and analysis is laborious due to the size datasets. Here, we introduce VesselExpress, an automated software that reliably analyzes six characteristic vascular network parameters including vessel diameter in LSFM on average computing hardware. VesselExpress ∼100 times faster than other existing tools, requires no user interaction, integrates batch...
Over the past decade, deep learning (DL) research in computer vision has been growing rapidly, with many advances DL-based image analysis methods for biomedical problems. In this work, we introduce MMV_Im2Im, a new open-source Python package image-to-image transformation bioimaging applications. MMV_Im2Im is designed generic framework that can be used wide range of tasks, including semantic segmentation, instance restoration, generation, and so on. Our implementation takes advantage...
The iris is a stable biometric trait that has been widely used for human recognition in various applications. However, deployment of forensic applications not reported. A primary reason the lack human-friendly techniques comparison. To further promote use forensics, similarity between irises should be made visualizable and interpretable. Recently, human-in-the-loop system was developed, based on detecting matching crypts. Building this framework, we propose new approach crypts automatically....
Visible light-regulated metal-free polymerizations have attracted considerable attention for macromolecular syntheses in recent years. However, few organic photocatalysts show high efficiency and strict photocontrol cationic polymerizations. Herein, we introduce monophosphonium-doped polycyclic arenes as an photocatalyst, which features the tunability, broad redox window, long excited state lifetime, excellent temporal control reversible addition–fragmentation chain transfer polymerization...
By virtue of noninvasive regulations by light, photocontrolled polymerizations have attracted considerable attention for the precision synthesis macromolecules. However, a cationic polymerization with simultaneous photocontrol and tacticity-regulation remains elusive so far. Herein, we introduce an asymmetric ion-pairing photoredox catalysis strategy that allows development stereoselective concurrent light regulation first time. employing ion pair catalyst (PC+/*A–) consisting active cation...
Until now, the analysis of microvascular networks in reperfused ischemic brain has been limited due to tissue transparency challenges.
<title>Abstract</title> Selective plane illumination microscopy (SPIM, also known as light sheet fluorescence microscopy) is the method of choice for studying organ morphogenesis and function, it permits gentle rapid volumetric imaging biological specimens over days. In inhomogeneous samples, however, sample-induced aberrations, including absorption, scattering, refraction, can degrade image, particularly focal gets deeper into sample. Here, we present Leonardo, first toolbox capable...
Abstract Infection with enterohemorrhagic E. coli (EHEC) causes severe changes in the brain leading to angiopathy, encephalopathy and microglial activation. In this study, we investigated role of tumour necrosis factor alpha (TNF-α) for activation pathology using a preclinical mouse model EHEC infection. LC–MS/MS proteomics mice injected combination Shiga toxin (Stx) lipopolysaccharide (LPS) revealed extensive alterations proteome, particular enrichment pathways involved complement...