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

An International Survey Among Attending Urologists on the Term High-Grade Prostatic Intraepithelial Neoplasia: Advocating for Removal of 'High-Grade' From the Surgical Pathology Report.

International journal of urology : official journal of the Japanese Urological Association·2026
Same author

Association Between Dietary Folate and Prostate Cancer Aggressiveness Among African Americans and European Americans.

Nutrients·2026
Same author

Multimodal deep learning for objective skill assessment in robot-assisted vesico-urethral anastomosis.

Journal of robotic surgery·2026
Same author

Integrating Pathogenic Variants, Polygenic Risk Score, and Family History for Prostate Cancer Risk Estimation in Men of African Ancestry.

European urology·2025
Same author

Mutational landscape of triple-negative breast cancer in African American women.

Nature genetics·2025
Same author

Associations of DNA methylation in breast tumour subtypes with parity and breastfeeding in a cohort of 1459 Black women: implications for public health.

BMJ oncology·2025

Related Experiment Video

Updated: Jun 3, 2026

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
08:40

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Published on: April 8, 2016

Variability in visual segmentation of digitized prostate tissue microarray cores.

Michael J Ray1, Swaroop S Singh, Warren Davis

  • 1Department of Cancer Prevention and Population Science, Roswell Park Cancer Institute, Buffalo, New York 14263, USA. michael.ray@roswellpark.org

Analytical and Quantitative Cytology and Histology
|April 5, 2011
PubMed
Summary
This summary is machine-generated.

Semi-automated machine vision systems in quantitative histometry show bias due to inter-segmenter variation. Reviewing current quality assurance is crucial to eliminate operator effects in these systems.

More Related Videos

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment
13:01

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

Related Experiment Videos

Last Updated: Jun 3, 2026

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
08:40

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Published on: April 8, 2016

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment
13:01

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

Area of Science:

  • Digital pathology
  • Quantitative histometry
  • Machine vision

Background:

  • Human-interactive semi-automated systems are increasingly used in quantitative histometry.
  • Machine vision components are key to these systems, aiming for objective measurements.
  • However, potential biases associated with human interaction require careful examination.

Purpose of the Study:

  • To investigate and quantify bias introduced by human-interactive components in semi-automated machine vision systems used for quantitative histometry.
  • To assess the impact of segmenter variability, time, and image orientation on measurements.

Main Methods:

  • A standardized image set of 20 nuclei from benign prostate tissue was used.
  • Four trained technicians performed image segmentation across multiple sessions and rotational orientations.
  • Measurements of nuclear area (NA), nuclear roundness factor (NRF), and mean optical density (MOD) were compared.

Main Results:

  • Significant variations in NA, NRF, and MOD were observed across different sessions and segmenters.
  • Inter-segmenter and intra-session differences were statistically significant for NRF.
  • MOD also showed significant variation among sessions and within sessions.

Conclusions:

  • Semi-automated machine vision systems remain susceptible to statistical inter-segmenter variation.
  • Statistically significant variations can introduce bias into morphometric analysis.
  • Current quality assurance practices need revision to mitigate individual operator effects.