title: PALMER: a method capable of parallel localization of multiple emitters for high-density localization microscopy.
abstract: Developing methods for high-density localization of multiple emitters is a promising approach for enhancing the temporal resolution of localization microscopy while maintaining a desired spatial resolution, but the widespread use of this approach is thus far mainly obstructed by the slow image analysis speed. Here we present a high-density localization method based on the combination of Graphics Processing Unit (GPU) parallel computation, multiple-emitter fitting, and model recommendation via Bayesian Information Criterion (BIC). This method, called PALMER, exhibits satisfactory localization accuracy comparable with the previous reported SSM_BIC method, while executes more than two orders of magnitudes faster. Meanwhile, compared to the conventional localization microscopy which is based on sparse emitter localization, high-density localization microscopy based the PALMER method allows a speed gain of up to ~14-fold in obtaining a super-resolution image with the same Nyquist resolution.
authors: Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China.
authors: Yina
authors: Y
authors: Wang
authors: Tingwei
authors: T
authors: Quan
authors: Shaoqun
authors: S
authors: Zeng
authors: Zhen-Li
authors: ZL
authors: Huang
mesh_terms: D001499:Bayes Theorem; D003196:Computer Graphics; D003198:Computer Simulation; D007091:Image Processing, Computer-Assisted; D008853:Microscopy / Q000295:instrumentation* / Q000379:methods*; D013997:Time Factors