Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Algorithm to estimate cell biovolume using image analyzed microscopy.

M E Sieracki1, C L Viles, K L Webb

  • 1School of Marine Science, College of William and Mary, Virginia Institute of Marine Science, Gloucester Point 23062.

Cytometry
|September 1, 1989
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Single cell genomics yields a wide diversity of small planktonic protists across major ocean ecosystems.

Scientific reports·2019
Same author

Disciplinary boundaries and integrating care: using Q-methodology to understand trainee views on being a good doctor.

BMC medical education·2019
Same author

Community characteristics modify the relationship between obesity prevention efforts and dietary intake in children: the Healthy Communities Study.

Pediatric obesity·2018
Same author

Associations of community programs and policies with children's dietary intakes: the Healthy Communities Study.

Pediatric obesity·2018
Same author

Objectives of community policies and programs associated with more healthful dietary intakes among children: findings from the Healthy Communities Study.

Pediatric obesity·2018
Same author

'It's surprising how differently they treat you': a qualitative analysis of trainee reflections on a new programme for generalist doctors.

BMJ open·2016
Same journal

Measurement of the distribution of red blood cell deformability using an automated rheoscope.

Cytometry·2002
Same journal

Flow cytometric-based isolation of nucleated erythroid cells during maturation: an approach to cell surface antigen studies.

Cytometry·2002
Same journal

Flow cytometric immunophenotyping test for staging/monitoring neuroblastoma patients.

Cytometry·2002
Same journal

Determination of bronchoalveolar lavage leukocyte populations by flow cytometry in patients investigated for respiratory disease.

Cytometry·2002
Same journal

Multicenter clinical experience with flow cytometric method for fetomaternal hemorrhage detection.

Cytometry·2002
Same journal

Separation of live cells in different phases of the cell cycle for gene expression analysis.

Cytometry·2002
See all related articles

This study introduces a novel algorithm for calculating microbial cell biovolume from 2D images. The method digitally reconstructs cell shape, offering a more accurate alternative to traditional geometrical formulas.

Area of Science:

  • Microbiology
  • Image Analysis
  • Cell Biology

Background:

  • Accurate biovolume estimation is crucial for microbial ecology and physiology.
  • Conventional methods using length, width, and geometrical formulas often oversimplify cell shapes.
  • Existing image analysis techniques may lack the precision to capture cellular irregularities.

Purpose of the Study:

  • To develop and validate a new algorithm for calculating cell biovolume from 2D digital images.
  • To provide a method adaptable to various image analysis systems.
  • To improve biovolume calculation accuracy by accounting for complex cell morphologies.

Main Methods:

  • Algorithm utilizes 2D digital images of cells (e.g., bacteria, flagellates, ciliates).
  • Cell images are accessed as pixel data and rotated to a standard horizontal orientation.

Related Experiment Videos

  • A solid of revolution is computed via digital integration, approximating cell volume.

    • Main Results:

    • The algorithm successfully calculates biovolume for simple-shaped cells.
    • Method demonstrates adaptability across different image analysis platforms.
    • Verification confirms improved accuracy over conventional geometrical approaches.

    Conclusions:

    • The developed digital integration algorithm offers a more accurate biovolume estimation.
    • This method effectively addresses limitations of traditional biovolume calculations.
    • The algorithm provides a valuable tool for microbial research requiring precise cell volume data.