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 Concept Videos

You might also read

Related Articles

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

Sort by
Same author

A Phase 1 Study of Convection-Enhanced Delivery of Intraputaminal AAV2-GDNF in Advanced Parkinson's Disease.

Movement disorders : official journal of the Movement Disorder Society·2026
Same author

Chiari malformation type 0: methodological concerns regarding the null structural finding.

Acta neurochirurgica·2026
Same author

Weak-to-strong generalization enables fully automated training of multi-head mask-RCNN model for segmenting densely overlapping cell nuclei in multiplex whole-slice brain images.

Frontiers in bioinformatics·2026
Same author

PRMT5 inhibition impairs Fanconi Anemia pathway-mediated homologous recombination and enhances the antitumor efficacy of Temozolomide in glioblastoma.

Cell death & disease·2026
Same author

Ser423-phosphorylated MECP2 (MECP2-pS423) accumulates in human brain, cerebrospinal fluid and serum in sporadic Alzheimer's disease.

Acta neuropathologica·2026
Same author

Computational delineation and cellular profiling of murine cortical cell layers using multiplex immunofluorescence imaging.

Journal of neuroscience methods·2026

Related Experiment Video

Updated: May 21, 2025

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
07:05

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Published on: February 15, 2022

2.5K

Optimizing Colocalized Cell Counting Using Automated and Semiautomated Methods.

Hasita V Nalluri1, Shantelle A Graff2, Dragan Maric3

  • 1Surgical Neurology Branch, Flow and Imaging Cytometry Core Facility, Bethesda, MD, USA.

Neuroinformatics
|March 21, 2025
PubMed
Summary
This summary is machine-generated.

Automated and semi-automated object-based colocalization analysis (OBCA) reliably quantify immune cells in spinal arachnoid tissue. These methods significantly reduce analysis time compared to manual counting, proving valuable for large histological datasets.

Keywords:
ColocalizationQuantificationTissue

More Related Videos

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins
11:01

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

Published on: November 17, 2016

46.8K
Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone
09:31

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

Published on: April 8, 2015

11.5K

Related Experiment Videos

Last Updated: May 21, 2025

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
07:05

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Published on: February 15, 2022

2.5K
Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins
11:01

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

Published on: November 17, 2016

46.8K
Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone
09:31

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

Published on: April 8, 2015

11.5K

Area of Science:

  • Neuroimmunology
  • Histopathology
  • Computational Biology

Background:

  • Spinal subarachnoid space inflammation causes arachnoid hypercellularity.
  • Multiplex immunohistochemistry (MP-IHC) quantifies immune cells but manual counting is biased and time-consuming.
  • Existing automated methods face challenges with cell morphology and colocalization accuracy.

Purpose of the Study:

  • To evaluate semi-automated and automated Object-Based Colocalization Analysis (OBCA) for quantifying immune cells in human arachnoid tissue.
  • To compare OBCA methods with manual counting in terms of accuracy, reliability, and efficiency.
  • To assess the utility of OBCA for analyzing histological samples with diverse cell morphologies.

Main Methods:

  • Semi-automated and automated OBCA techniques were applied to human arachnoid tissue sections.
  • Immune cell colocalization was quantified using both OBCA methods and manual counting.
  • Statistical analysis, including correlation (R²), was used to compare the methods.

Main Results:

  • Both semi-automated and automated OBCA demonstrated high reliability across various cell morphologies (P < 0.0001).
  • Automated counts showed strong correlation with manual counts (R² = 0.7764-0.9954), indicating reliability for non-critical exact counts.
  • Both OBCA techniques significantly reduced analysis time compared to manual counting.

Conclusions:

  • Automated and semi-automated OBCA are reliable and efficient tools for quantifying immune cells in histological samples.
  • These methods offer a significant time-saving advantage over manual counting, especially for large datasets.
  • OBCA is recommended for analyzing immune cell infiltration in conditions like spinal arachnoid inflammation.