ArticleBiomedical optics express2021
Computational framework for generating large panoramic super-resolution images from localization microscopy.
Article in Biomedical optics express, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Image stitching algorithm for super-resolution localization microscopy combined with fluorescence noise prior.Biomedical optics express · 2024Article
- Multiplexed and Millimeter-Scale Fluorescence Nanoscopy of Cells and Tissue Sections via Prism-Illumination and Microfluidics-Enhanced DNA-PAINT.Chemical & biomedical imaging · 2023Article
- Field-dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging.Nature methods · 2023Article
- PCIe-based FPGA-GPU heterogeneous computation for real-time multi-emitter fitting in super-resolution localization microscopy.Biomedical optics express · 2022Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Combining super-resolution localization microscopy with pathology creates new opportunities for biomedical researches. This combination requires a suitable image mosaic method for generating a panoramic image from many overlapping super-resolution images. However, current image mosaic methods are not suitable for this purpose. Here we proposed a computational framework and developed an image mosaic method called NanoStitcher. We generated ground truth datasets and defined criteria to evaluate this computational framework. We used both simulated and experimental datasets to prove that NanoStitcher exhibits better performance than two representative image mosaic methods. This study is helpful for the mature of super-resolution digital pathology.
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Registered trials
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