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

Fairness aware subset selection for advancing equity in skin cancer detection.

Journal of the American Medical Informatics Association : JAMIA·2026
Same author

Towards interpretable prediction of recurrence risk in breast cancer using pathology foundation models.

NPJ digital medicine·2026
Same author

AI-driven prediction of progression to oral squamous cell carcinoma using a multiresolution pathology model.

NPJ digital medicine·2025
Same author

Environment Scan of Generative AI Infrastructure for Clinical and Translational Science.

ArXiv·2025
Same author

The Association of Long COVID and CKD: Findings from the National Clinical Cohort Collaborative.

Clinical journal of the American Society of Nephrology : CJASN·2025
Same author

Pathomics Image Analysis of Tumor Infiltrating Lymphocytes (TILs) in Colon Cancer.

Research square·2025
Same journal

LEARNABLE HIERARCHICAL VISUAL CONTEXTS FOR TUMOR SEGMENTATION IN COMPUTED TOMOGRAPHY IMAGES.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same journal

DUAL CROSS-ATTENTION SIAMESE TRANSFORMER FOR RECTAL TUMOR REGROWTH ASSESSMENT IN WATCH-AND-WAIT ENDOSCOPY.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same journal

LUMEN: LONGITUDINAL MULTI-MODAL RADIOLOGY MODEL FOR PROGNOSIS AND DIAGNOSIS.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same journal

OVERVIEW OF THE CXR-LT 2026 CHALLENGE: MULTI-CENTER LONG-TAILED AND ZERO SHOT CHEST X-RAY CLASSIFICATION.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same journal

CROSS-MODAL FINE-TUNING OF 3D CONVOLUTIONAL FOUNDATION MODELS FOR ADHD CLASSIFICATION WITH LOW-RANK ADAPTATION.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same journal

AN IN SILICO STUDY OF LOW-INTENSITY FOCUSED ULTRASOUND DISPLACEMENT MAPPING WITH A 220 KHZ CLINICAL PHASED-ARRAY TRANSDUCER.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
See all related articles

Related Experiment Video

Updated: Jun 18, 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

A caGRID-ENABLED, LEARNING BASED IMAGE SEGMENTATION METHOD FOR HISTOPATHOLOGY SPECIMENS.

David J Foran1, Lin Yang, Oncel Tuzel

  • 1The Cancer Institute of New Jersey, UMDNJ-RWJMS, Piscataway, NJ 08854.

Proceedings. IEEE International Symposium on Biomedical Imaging
|November 26, 2009
PubMed
Summary
This summary is machine-generated.

This study presents a fast, accurate algorithm for segmenting tissue microarrays, achieving 90% accuracy in identifying tumor regions. The automated system enhances computational efficiency for digital pathology workflows.

More Related Videos

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
10:59

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands

Published on: July 26, 2014

Generating and Analyzing High-Parameter Histology Images with Histoflow Cytometry
05:22

Generating and Analyzing High-Parameter Histology Images with Histoflow Cytometry

Published on: June 21, 2024

Related Experiment Videos

Last Updated: Jun 18, 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

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
10:59

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands

Published on: July 26, 2014

Generating and Analyzing High-Parameter Histology Images with Histoflow Cytometry
05:22

Generating and Analyzing High-Parameter Histology Images with Histoflow Cytometry

Published on: June 21, 2024

Area of Science:

  • Digital Pathology
  • Computational Biology
  • Medical Image Analysis

Background:

  • Accurate segmentation of tissue microarrays is difficult due to tissue similarities.
  • Processing speed is critical for large-volume digital pathology slide analysis.

Purpose of the Study:

  • To develop a fast and accurate image segmentation algorithm for tissue microarrays.
  • To enable efficient and precise identification of tumor regions within digital pathology images.

Main Methods:

  • Introduced a whole disc delineation algorithm.
  • Utilized a learning-based tumor region segmentation approach with multi-scale texton histograms.
  • Implemented an analytical service using caGrid for remote access and collaboration.

Main Results:

  • Achieved a mean pixel-wise segmentation accuracy of approximately 90%.
  • Demonstrated computational efficiency: 1 second for whole disc segmentation (1024x1024 pixels).
  • Showcased rapid tumor region segmentation in under 5 seconds.

Conclusions:

  • The developed algorithm is automatic, computationally efficient, and highly accurate for tissue microarray segmentation.
  • The caGrid-based service facilitates remote analysis and collaborative research in digital pathology.
  • This approach significantly improves processing speed and accuracy in analyzing digitized tissue slides.