Computational Imaging Researcher | Pushing the boundaries of super-resolution microscopy
- Name: Tai-Long Chen
- Role: Computational Imaging Researcher
- Current focus: NP-Cloud drift correction for SMLM
- Research interests: SMLM, Super-Resolution Imaging, Deep Learning for Microscopy, Ultrasound Localization, PSF Modeling, Drift Correction
- Languages: Python, MATLAB, Julia, C++/CUDA
| 🧬 SMLM | 🎯 Drift Correction | 🫀 Ultrasound Microscopy |
| Single Molecule Localization Microscopy with nanometer precision | Computational methods for sample drift correction in long acquisitions | Super-resolution concepts for ultrasound imaging of microvasculature |
| 🧠 Deep Learning | 🔭 PSF Engineering | 📊 Image Analysis |
| Neural networks for image reconstruction, denoising and segmentation | Point spread function modeling for 3D localization microscopy | Quantitative analysis, velocimetry, and statistical methods |
Languages
Frameworks & Tools
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Python implementation of NP-Cloud drift correction for SMLM. A robust computational method for correcting sample drift using nanoparticle fiducial markers.
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Image segmentation tools and algorithms for microscopy data analysis and biological image processing.
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PALA ⭐OPUS-PALA & LOTUS tools for ultrasound localization microscopy analysis.
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Datasets and benchmarks in SMLM for AI research, training, and education.
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- 🔗 GitHub: @Tailong-Chen
- 🌐 Website: tailong-chen.github.io
💬 Open to research collaborations in computational imaging and microscopy!