Field dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging
This paper introduces FD-DeepLoc, a deep learning method for high-throughput 3D super-resolution imaging over a large field of view using a sCMOS camera.
Author
Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.
5 papers
Recent·Most cited
This paper introduces FD-DeepLoc, a deep learning method for high-throughput 3D super-resolution imaging over a large field of view using a sCMOS camera.
Y. Wang, W. Kuang, M. Shang, Z.-L. Huang
This paper introduces a two-color super-resolution microscopy method using an RGBW camera and joint encoding of emitter location and color, achieving ~20 nm resolution and <2% crosstalk.
Z. Zhang, Y. Wang, R. Piestun, Z.-L. Huang
This study characterizes and corrects noise non-uniformity in back-illuminated sCMOS cameras, showing that corrections can improve image quality for microscopy applications.
M.-H. Luo, B. Yang, Y. Yao…·S. Gong
This paper shows HCMV drives WDR5 to the virion assembly compartment to facilitate virion assembly, expanding its role beyond nuclear egress.
L. Li, B. Xin, W. Kuang…·Z.-L. Huang
This paper introduces QC-STORM, a real-time multi-emitter localization method for super-resolution microscopy, achieving comparable resolution to existing methods on small images.