Open AccessAutomated Motion Tracking and Data Extraction for Red Blood Cell Biomechanics
Author(s) -
Kumar Arun,
Schmidt Brendan R.,
Sanchez Zyrina Alura C.,
Yazar Feyza,
Davis Ronald W.,
Ramasubramanian Anand K.,
Saha Amit K.
Publication year - 2020
Publication title -
current protocols in cytometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.718
H-Index - 26
eISSN - 1934-9300
pISSN - 1934-9297
DOI - 10.1002/cpcy.75
Subject(s) - computer science , protocol (science) , automation , workflow , tracking (education) , computer vision , red blood cell , software , artificial intelligence , biomedical engineering , pathology , medicine , engineering , psychology , pedagogy , mechanical engineering , alternative medicine , database , programming language
Red blood cell biomechanics can provide us with a deeper understanding of macroscopic physiology and have the potential of being used for diagnostic purposes. In diseases like sickle cell anemia and malaria, reduced red blood cell deformability can be used as a biomarker, leading to further assays and diagnoses. A microfluidic system is useful for studying these biomechanical properties. We can observe detailed red blood cell mechanical behavior as they flow through microcapillaries using high‐speed imaging and microscopy. Microfluidic devices are advantageous over traditional methods because they can serve as high‐throughput tests. However, to rapidly analyze thousands of cells, there is a need for powerful image processing tools and software automation. We describe a workflow process using Image‐Pro to identify and track red blood cells in a video, take measurements, and export the data for use in statistical analysis tools. The information in this protocol can be applied to large‐scale blood studies where entire cell populations need to be analyzed from many cohorts of donors. © 2020 The Authors. Basic Protocol 1 : Enhancing raw video for motion tracking Basic Protocol 2 : Extracting motion tracking data from enhanced video