ArticleMedical image analysis2016
Automatic optimal filament segmentation with sub-pixel accuracy using generalized linear models and B-spline level-sets.
Article in Medical image analysis, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- KnotResolver: tracking self-intersecting filaments in microscopy using directed graphs.Bioinformatics (Oxford, England) · 2024Article
- Quantifying Yeast Microtubules and Spindles Using the Toolkit for Automated Microtubule Tracking (TAMiT).Biomolecules · 2023Article
- Tracing and tracking filamentous structures across scales: A systematic review.Computational and structural biotechnology journal · 2023Review
- The rate of microtubule breaking increases exponentially with curvature.Scientific reports · 2022Article
- Measuring expression heterogeneity of single-cell cytoskeletal protein complexes.Nature communications · 2021Article
- Automated and semi-automated enhancement, segmentation and tracing of cytoskeletal networks in microscopic images: A review.Computational and structural biotechnology journal · 2021Review
- Modelling Motility: The Mathematics of Spermatozoa.Frontiers in cell and developmental biology · 2021Review
- Prior-Apprised Unsupervised Learning of Subpixel Curvilinear Features in Low Signal/Noise Images.Biophysical journal · 2020Article
- Automated identification of flagella from videomicroscopy via the medial axis transform.Scientific reports · 2019Article
- MTrack: Automated Detection, Tracking, and Analysis of Dynamic Microtubules.Scientific reports · 2019Article
- Lack of GAS2L2 Causes PCD by Impairing Cilia Orientation and Mucociliary Clearance.American journal of human genetics · 2019Article
- LimeSeg: a coarse-grained lipid membrane simulation for 3D image segmentation.BMC bioinformatics · 2019Article
- Rapid time-stamped analysis of filament motility.Journal of muscle research and cell motility · 2018Article
- Convolutional neural networks automate detection for tracking of submicron-scale particles in 2D and 3D.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Integrated one- and two-photon scanned oblique plane illumination (SOPi) microscopy for rapid volumetric imaging.Optics express · 2018Article
- Hyperspectral imaging: a novel approach for plant root phenotyping.Plant methods · 2018Article
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Authors and funding
5 authors.
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Abstract
Biological filaments, such as actin filaments, microtubules, and cilia, are often imaged using different light-microscopy techniques. Reconstructing the filament curve from the acquired images constitutes the filament segmentation problem. Since filaments have lower dimensionality than the image itself, there is an inherent trade-off between tracing the filament with sub-pixel accuracy and avoiding noise artifacts. Here, we present a globally optimal filament segmentation method based on B-spline vector level-sets and a generalized linear model for the pixel intensity statistics. We show that the resulting optimization problem is convex and can hence be solved with global optimality. We introduce a simple and efficient algorithm to compute such optimal filament segmentations, and provide an open-source implementation as an ImageJ/Fiji plugin. We further derive an information-theoretic lower bound on the filament segmentation error, quantifying how well an algorithm could possibly do given the information in the image. We show that our algorithm asymptotically reaches this bound in the spline coefficients. We validate our method in comprehensive benchmarks, compare with other methods, and show applications from fluorescence, phase-contrast, and dark-field microscopy.
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