ABSTRACT
The Cell Tracking Challenge is an ongoing benchmarking initiative that has become a reference in cell segmentation and tracking algorithm development. Here, we present a significant number of improvements introduced in the challenge since our 2017 report. These include the creation of a new segmentation-only benchmark, the enrichment of the dataset repository with new datasets that increase its diversity and complexity, and the creation of a silver standard reference corpus based on the most competitive results, which will be of particular interest for data-hungry deep learning-based strategies. Furthermore, we present the up-to-date cell segmentation and tracking leaderboards, an in-depth analysis of the relationship between the performance of the state-of-the-art methods and the properties of the datasets and annotations, and two novel, insightful studies about the generalizability and the reusability of top-performing methods. These studies provide critical practical conclusions for both developers and users of traditional and machine learning-based cell segmentation and tracking algorithms.
Subject(s)
Benchmarking , Cell Tracking , Cell Tracking/methods , Machine Learning , AlgorithmsABSTRACT
Accurate segmentation and tracking of cells in microscopy image sequences is extremely beneficial in clinical diagnostic applications and biomedical research. A continuing challenge is the segmentation of dense touching cells and deforming cells with indistinct boundaries, in low signal-to-noise-ratio images. In this paper, we present a dual-stream marker-guided network (DMNet) for segmentation of touching cells in microscopy videos of many cell types. DMNet uses an explicit cell marker-detection stream, with a separate mask-prediction stream using a distance map penalty function, which enables supervised training to focus attention on touching and nearby cells. For multi-object cell tracking we use M2Track tracking-by-detection approach with multi-step data association. Our M2Track with mask overlap includes short term track-to-cell association followed by track-to-track association to re-link tracklets with missing segmentation masks over a short sequence of frames. Our combined detection, segmentation and tracking algorithm has proven its potential on the IEEE ISBI 2021 6th Cell Tracking Challenge (CTC-6) where we achieved multiple top three rankings for diverse cell types. Our team name is MU-Ba-US, and the implementation of DMNet is available at, http://celltrackingchallenge.net/participants/MU-Ba-US/.
ABSTRACT
Precise positioning of neurons resulting from cell division and migration during development is critical for normal brain function. Disruption of neuronal migration can cause a myriad of neurological disorders. To investigate the functional consequences of defective neuronal positioning on circuit function, we studied a zebrafish frizzled3a (fzd3a) loss-of-function mutant off-limits (olt) where the facial branchiomotor (FBM) neurons fail to migrate out of their birthplace. A jaw movement assay, which measures the opening of the zebrafish jaw (gape), showed that the frequency of gape events, but not their amplitude, was decreased in olt mutants. Consistent with this, a larval feeding assay revealed decreased food intake in olt mutants, indicating that the FBM circuit in mutants generates defective functional outputs. We tested various mechanisms that could generate defective functional outputs in mutants. While fzd3a is ubiquitously expressed in neural and non-neural tissues, jaw cartilage and muscle developed normally in olt mutants, and muscle function also appeared to be unaffected. Although FBM neurons were mispositioned in olt mutants, axon pathfinding to jaw muscles was unaffected. Moreover, neuromuscular junctions established by FBM neurons on jaw muscles were similar between wildtype siblings and olt mutants. Interestingly, motor axons innervating the interhyoideus jaw muscle were frequently defasciculated in olt mutants. Furthermore, GCaMP imaging revealed that mutant FBM neurons were less active than their wildtype counterparts. These data show that aberrant positioning of FBM neurons in olt mutants is correlated with subtle defects in fasciculation and neuronal activity, potentially generating defective functional outputs.