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

Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an organic...

You might also read

Related Articles

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

Sort by
Same author

Comparing incidence of heart failure in individuals with enlarged cardiac chambers versus diabetes.

American journal of preventive cardiology·2026
Same author

AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis.

Radiology. Cardiothoracic imaging·2026
Same author

Assessment of the aortic root and ascending aorta in swine using CTA.

Cardiovascular journal of Africa·2026
Same author

Patient-specific timing acquisition for coronary CT angiography: A retrospective patient validation study.

European journal of radiology open·2026
Same author

Accurate iodine quantification and residual error reduction with principal component analysis multimaterial decomposition using spectral CT.

Medical physics·2026
Same author

AI-Derived LA Volume Index, LA/RA and LA/LV Volume Ratios From Coronary Artery Calcium Scans Predict Long-Term Atrial Fibrillation and Stroke.

Stroke·2026

Related Experiment Video

Updated: Jun 4, 2026

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine
08:27

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Least squares parameter estimation methods for material decomposition with energy discriminating detectors.

Q Le Huy1, Sabee Molloi

  • 1Department of Radiological Sciences, University of California, Irvine, California 92697, USA.

Medical Physics
|March 3, 2011
PubMed
Summary

Energy resolving detectors and calibrated least squares minimization accurately decompose four materials in breast imaging. This technique successfully separates and quantifies hydroxyapatite and iodine concentrations, improving diagnostic accuracy.

More Related Videos

Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
06:50

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

Published on: November 8, 2019

Related Experiment Videos

Last Updated: Jun 4, 2026

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine
08:27

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
06:50

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

Published on: November 8, 2019

Area of Science:

  • Medical Imaging
  • Detector Physics
  • Computational Imaging

Background:

  • Energy resolving detectors offer multi-spectral measurements per acquisition.
  • Accurate material decomposition is crucial for advanced breast imaging analysis.

Purpose of the Study:

  • To investigate material decomposition capabilities using energy discriminating detectors.
  • To evaluate least squares minimization techniques for four-material decomposition in breast imaging.

Main Methods:

  • Simulated computed tomography (CT) with a CdZnTe (CZT) detector and an 80 kVp spectrum.
  • Investigated three least squares parameter estimation techniques, including a calibrated method.
  • Embedded hydroxyapatite and iodine contrast agents in digital breast phantoms.

Main Results:

  • A calibrated least squares technique achieved good separation and quantification of four materials.
  • Quantification accuracy showed low errors for hydroxyapatite (9.83%) and iodine (6.61%).
  • Multi-point calibration significantly reduced errors across various breast sizes (8-20 cm diameter).

Conclusions:

  • CT systems with CZT detectors and calibrated least squares minimization can effectively decompose four materials.
  • The calibrated technique provides accurate separation and quantification of hydroxyapatite and iodine concentrations.
  • This approach enhances the potential for detailed material analysis in breast imaging.