ArticleProceedings. International Conference on Image Processing2020
QUANTIFYING ACTIN FILAMENTS IN MICROSCOPIC IMAGES USING KEYPOINT DETECTION TECHNIQUES AND A FAST MARCHING ALGORITHM.
Article in Proceedings. International Conference on Image Processing, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- From Pixels to Patterns: A Multidimensional Framework to Decode Cytoskeletal Organization.Computational and structural biotechnology journal · 2026Review
- A novel computational approach to dissect the cytoskeletal architecture of cancer cells with invasive potential.Scientific reports · 2025Article
- Smart Home Automation-Based Hand Gesture Recognition Using Feature Fusion and Recurrent Neural Network.Sensors (Basel, Switzerland) · 2023Article
- ILEE: Algorithms and toolbox for unguided and accurate quantitative analysis of cytoskeletal images.The Journal of cell biology · 2023Article
- FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking.PloS one · 2023Article
- Automated and semi-automated enhancement, segmentation and tracing of cytoskeletal networks in microscopic images: A review.Computational and structural biotechnology journal · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
The actin filament plays a fundamental role in numerous cellular processes such as cell growth, proliferation, migration, division, and locomotion. The actin cytoskeleton is highly dynamical and can polymerize and depolymerize in a very short time under different stimuli. To study the mechanics of actin filament, quantifying the length and number of actin filaments in each time frame of microscopic images is fundamental. In this paper, we adopt a Convolutional Neural Network (CNN) to segment actin filaments first, and then we utilize a modified Resnet to detect junctions and endpoints of filaments. With binary segmentation and detected keypoints, we apply a fast marching algorithm to obtain the number and length of each actin filament in microscopic images. We have also collected a dataset of 10 microscopic images of actin filaments to test our method. Our experiments show that our approach outperforms other existing approaches tackling this problem regarding both accuracy and inference time.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.