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

Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

8.0K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
8.0K
Atomic Absorption Spectroscopy: Interference01:25

Atomic Absorption Spectroscopy: Interference

1.9K
Interference leads to systematic error in atomic absorption (AA) measurements by enhancing or diminishing the analytical signal or the background. These interferences can be grouped into three main categories: spectral interference, chemical interference, and physical interference.
Spectral interference occurs when signals from other elements or molecules overlap with the analyte signal, falsely elevating or masking the analyte's absorbance. This interference can be corrected using Zeeman,...
1.9K

You might also read

Related Articles

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

Sort by
Same author

The confounding effects of skin colour in photoacoustic imaging.

Nature communications·2026
Same author

SPEND-hSRS imaging of fumarate uncovers mitochondrial metabolic heterogeneity.

bioRxiv : the preprint server for biology·2026
Same author

Using Electrostatic Mapping to Understand PANI-MWCNTs' NH<sub>3</sub> Sensing.

Sensors (Basel, Switzerland)·2026
Same author

Early Radiation Therapy Response Assessment Using Multi-Scale Photoacoustic Imaging.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Optical coherence tomography and elastography for <i>ex vivo</i> visualization of early gastric cancer.

Journal of biomedical optics·2026
Same author

Harnessing Plant-Based Nanoparticles for Targeted Therapy: A Green Approach to Cancer and Bacterial Infections.

International journal of molecular sciences·2025

Related Experiment Video

Updated: Dec 26, 2025

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

2.7K

A background correction method to compensate illumination variation in hyperspectral imaging.

Jonghee Yoon1,2, Alexandru Grigoroiu1,2, Sarah E Bohndiek1,2

  • 1Department of Physics, University of Cambridge, Cambridge, England, United Kingdom.

Plos One
|March 14, 2020
PubMed
Summary

This study introduces a new background correction method for hyperspectral imaging (HSI) to improve disease diagnosis. The technique compensates for variations in illumination, enhancing the reliability of HSI in complex biological settings.

More Related Videos

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
07:34

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

8.3K
High-Accuracy Correction of 3D Chromatic Shifts in the Age of Super-Resolution Biological Imaging Using Chromagnon
08:18

High-Accuracy Correction of 3D Chromatic Shifts in the Age of Super-Resolution Biological Imaging Using Chromagnon

Published on: June 16, 2020

7.9K

Related Experiment Videos

Last Updated: Dec 26, 2025

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

2.7K
Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
07:34

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

8.3K
High-Accuracy Correction of 3D Chromatic Shifts in the Age of Super-Resolution Biological Imaging Using Chromagnon
08:18

High-Accuracy Correction of 3D Chromatic Shifts in the Age of Super-Resolution Biological Imaging Using Chromagnon

Published on: June 16, 2020

7.9K

Area of Science:

  • Biomedical optics
  • Medical imaging technology
  • Spectroscopy

Background:

  • Hyperspectral imaging (HSI) offers rich spatial and spectral data for biological tissues.
  • Complex biological environments and variable illumination complicate HSI data interpretation.
  • Existing HSI methods face challenges in accuracy due to surface topology and optical power variations.

Purpose of the Study:

  • To develop a robust background correction method for hyperspectral imaging.
  • To compensate for illumination variations in complex biological samples.
  • To enhance the diagnostic accuracy of HSI in clinical applications.

Main Methods:

  • Proposed a background correction algorithm using normalized spectral profiles and fixed-wavelength intensity.
  • Estimated optical properties of illumination at the target.
  • Validated the method on blood samples, tissue phantoms, and ex vivo chicken tissue.

Main Results:

  • Demonstrated the feasibility of the background correction method.
  • Showed improved statistical analysis of HSI data using synthetic data.
  • The method effectively compensates for variations in illumination and surface topology.

Conclusions:

  • The proposed background correction method enhances HSI reliability in challenging environments.
  • This technique can improve disease diagnostic capabilities by reducing post-processing errors.
  • Facilitates the clinical implementation of hyperspectral imaging where illumination control is limited.