Detection and tracking of migrating oligodendrocyte progenitor cells from in vivo fluorescence time-lapse imaging data.

DETECTION AND TRACKING OF MIGRATING OLIGODENDROCYTE PROGENITOR CELLS FROM IN VIVO FLUORESCENCE TIME-LAPSE IMAGING DATA.
Proc IEEE Int Symp Biomed Imaging. 2018 Apr;2018:961-964
Authors: Wang Y, Ali M, Wang Y, Kucenas S, Yu G
Abstract
In this work, we develop a fully automatic algorithm named "MCDT" (Migrating Cell Detector and Tracker) for the integrated task of migrating cell detection, segmentation and tracking from in vivo fluorescence time-lapse microscopy imaging data. The interest of detecting and tracking migrating cells arouses from the scientific question in understanding the impact of oligodendrocyte progenitor cells (OPCs) migration in vivo, using advanced microscopy imaging techniques. Current practice of OPC mobility analysis relies on manual labeling, suffering from massive human labor, subjective biases, and weak reproducibility. Existing cell tracking methods have difficulties in analyzing such challenging data due to the extra complexity of in vivo data. Designed for in vivo data, MCDT circumvents the common strong assumption of separable feature distributions between foreground and background. Besides, by focusing on migrating cells (OPCs) only, MCDT relieves the burden of tracking all irrelevant cells correctly, not only accelerating the analysis but also achieving better accuracy in OPCs. Seed based segmentation and tracking by topology-preserved motion estimation endows MCDT with robustness to complex surrounding...

Source: Proceedings - International Symposium on Biomedical Imaging - January 2, 2019 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research