Towards Automatic and Robust Particle Tracking in Microrheology Studies

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Campo Deano, L (Author) FEUP; Marina Castro (Author) Other; Ricardo J. Araújo (Author) Other; Oliveira, HP (Author) FCUP

Conference proceedings International

Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Pages: 508-519

9th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2019

1 July 2019 through 4 July 2019

Indexing

Scopus - 1 Citation

Other information

Authenticus ID: P-00R-2EG

DOI: 10.1007/978-3-030-31321-0_44

Abstract (EN): Particle tracking applied to video passive microrheology is conventionally done through methods that are far from being automatic. Creating mechanisms that decode the image set properties and correctly detect the tracer beads, to find their trajectories, is fundamental to facilitate microrheology studies. In this work, the adequacy of two particle detection methods - a Radial Symmetry-based approach and Gaussian fitting - for microrheology setups is tested, both on a synthetic database and on real data. Results show that it is possible to automate the particle tracking process in this scope, while ensuring high detection accuracy and sub-pixel precision, crucial for an adequate characterization of microrheology studies. © 2019, Springer Nature Switzerland AG.

Language: English

Type (Professor's evaluation): Scientific