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

Spectral imaging: principles and applications.

Yuval Garini1, Ian T Young, George McNamara

  • 1Quantitative Imaging Group, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands. y.garini@tudelft.nl

Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|September 14, 2006
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

Telomeres in Lamin-A-depleted cells exhibit directed motion and dynamic coherence.

Biophysical journal·2026
Same author

Using machine learning-based Natural Language Processing to quantify emergency department presentations related to suicide or self-harm in the Australian Capital Territory.

The Australian and New Zealand journal of psychiatry·2026
Same author

Thyroid cancer detection and classification using spectral imaging and artificial intelligence.

Scientific reports·2026
Same author

Engineering a Mechanoresponsive DNA Origami Capsule for Drug Delivery to Narrowed Arteries.

Nano letters·2026
Same author

Effects of cross-linking on spatial organization and dynamics of confined associating polymers.

Soft matter·2025
Same author

AI-Powered Spectral Imaging for Virtual Pathology Staining.

Bioengineering (Basel, Switzerland)·2025
Same journal

A Modular High-Parameter Flow Cytometry Framework: Pre-Analytical Optimization and Validation for Clinical Research.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Quantitative Detection of Entotic Cell-In-Cell Structures Using Deformable Segmentation and Deep Learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Comparison of Tissue Preparations to Identify and Phenotype T Cells in Human Colorectal Tumor Tissue.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Refractive Index-Correlated Pseudocoloring for Adaptive Color Fusion in Holotomographic Cytology.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Ensembling Unets for Rare Chromosomal Aberration Detection in Metaphase Images, Uncertainty Quantification, and Ionizing Radiation Dose Estimation.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

OMIP-121: Immune Phenotyping of Canine Peripheral Leukocytes by Mass Cytometry.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
See all related articles

Spectral imaging, combining spectroscopy and imaging, offers powerful qualitative and quantitative analysis for biological and clinical studies. This technique provides new insights into cellular components and proteins, though data analysis requires specialized algorithms.

Area of Science:

  • Multimodal imaging techniques
  • Spectroscopy and imaging integration

Background:

  • Spectral imaging enhances biological and clinical studies by enabling simultaneous qualitative and quantitative analysis of multiple features like organelles and proteins.
  • It merges spectroscopy and imaging, creating a powerful tool for advanced research.
  • Integrating dispersive optics with imaging equipment is necessary for spectral data acquisition, presenting specific technical constraints.

Purpose of the Study:

  • To describe the principles and applications of spectral imaging.
  • To highlight the necessity of specialized algorithms for analyzing complex spectral imaging data.
  • To evaluate the advantages of spectral imaging for specific experimental modes and applications.

Main Methods:

  • Discussion of spectral imaging principles and representative applications.

Related Experiment Videos

  • Exploration of algorithms for analyzing spectral imaging data, particularly for fluorescence and bright-field microscopy.
  • Evaluation of spectral imaging based on its utility in diverse scientific applications.

    • Main Results:

    • Spectral imaging facilitates detailed analysis of biological and clinical samples.
    • Complex spectral data necessitates computational analysis, with various algorithms available for different experimental setups.
    • The effectiveness of spectral imaging is demonstrated across several applications, showcasing its potential.

    Conclusions:

    • Spectral imaging is an emerging technique with significant, yet largely untapped, potential in scientific research.
    • Current applications already demonstrate the value and versatility of spectral imaging in diverse fields.