A fully-automated multiscale kernel graph cuts based particle localization scheme for temporal focusing two-photon microscopy

Proc SPIE Int Soc Opt Eng. 2017 Mar:10137:101371I. doi: 10.1117/12.2254567.

Abstract

The temporal focusing two-photon microscope (TFM) is developed to perform depth resolved wide field fluorescence imaging by capturing frames sequentially. However, due to strong nonignorable noises and diffraction rings surrounding particles, further researches are extremely formidable without a precise particle localization technique. In this paper, we developed a fully-automated scheme to locate particles positions with high noise tolerance. Our scheme includes the following procedures: noise reduction using a hybrid Kalman filter method, particle segmentation based on a multiscale kernel graph cuts global and local segmentation algorithm, and a kinematic estimation based particle tracking method. Both isolated and partial-overlapped particles can be accurately identified with removal of unrelated pixels. Based on our quantitative analysis, 96.22% isolated particles and 84.19% partial-overlapped particles were successfully detected.

Keywords: Diffraction ring; Kalman filter; Multiscale kernel graph cuts; Particle localization; Temporal focusing two-photon microscope (TFM).