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

Xia Huang; Chunqiang Li; Chuan Xiao; Wenqing Sun; Wei Qian

doi:10.1117/12.2254567

13 March 2017 A fully-automated multiscale kernel graph cuts based particle localization scheme for temporal focusing two-photon microscopy

Xia Huang, Chunqiang Li, Chuan Xiao, Wenqing Sun, Wei Qian

Author Affiliations +

Proceedings Volume 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging; 101371I (2017) https://doi.org/10.1117/12.2254567
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

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.

Conference Presentation

Citation Download Citation

Xia Huang, Chunqiang Li, Chuan Xiao, Wenqing Sun, and Wei Qian "A fully-automated multiscale kernel graph cuts based particle localization scheme for temporal focusing two-photon microscopy", Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 101371I (13 March 2017); https://doi.org/10.1117/12.2254567

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