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

Data Validation01:15

Data Validation

3.3K
Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
3.3K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

112.2K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
112.2K
Dose Size and Dosing Frequency: Determination Methods01:21

Dose Size and Dosing Frequency: Determination Methods

437
Determining the optimal dose size and dosing frequency in pharmacotherapy is crucial for achieving therapeutic effectiveness while minimizing adverse effects. This article explores the methodologies employed in determining these parameters, focusing on their significance and interplay to tailor dosing regimens.Dose Size: Dose size refers to the amount of a drug administered in a single dose. It is determined based on the drug's pharmacodynamics and pharmacokinetics properties and...
437
Estimation of k and VD of Aminoglycosides01:20

Estimation of k and VD of Aminoglycosides

286
Aminoglycosides are a class of antibiotics used to treat various bacterial infections. Clinicians must determine the elimination rate constant (k) and volume of distribution (VD) to optimize therapeutic efficacy and minimize toxicity. The k value represents the rate at which the drug is removed from the body, and the VD reflects the degree to which the drug distributes into body tissues. Accurately estimating these parameters allows healthcare professionals to tailor drug dosing to individual...
286

You might also read

Related Articles

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

Sort by
Same author

Suppression of macrophage enriched miRNA 210-3p improves cardiac fibrosis and cardiac function following myocardial infarction.

Clinical hemorheology and microcirculation·2026
Same author

Tumoral and Systemic Immune Correlates of Response to Concurrent Pembrolizumab and Chemoradiotherapy in Patients with Resected High-Risk Head and Neck Squamous Cell Carcinoma.

Clinical cancer research : an official journal of the American Association for Cancer Research·2026
Same author

A proof-of-concept automated method for accurate skin dosimetry: correcting overestimated surface dose measurements.

Physics in medicine and biology·2026
Same author

Novel Mechanism of and Therapeutic Approach for Anthracycline-Induced Cardiotoxicity.

Cancer research communications·2026
Same author

Comparative analysis of radiation therapy plans before and after biodegradable hydrogel (SpaceOAR) injection for reducing rectal toxicity in patients with prostate cancer undergoing carbon ion radiotherapy.

Frontiers in oncology·2026
Same author

Development and validation of an automated, accurate in-house treatment planning system for pencil-beam scanning carbon ion radiotherapy.

Medical physics·2026

Related Experiment Video

Updated: Mar 2, 2026

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.7K

Validating Dose Uncertainty Estimates Produced by AUTODIRECT: An Automated Program to Evaluate Deformable Image

Hojin Kim1,2, Josephine Chen1, Justin Phillips1

  • 1Department of Radiation Oncology, University of California, San Francisco, CA, USA.

Technology in Cancer Research & Treatment
|May 12, 2017
PubMed
Summary

This study validates an automated tool for deformable image registration confidence, showing it accurately predicts dose mapping errors in radiation therapy. The tool effectively estimates uncertainty in image registration algorithms for improved accuracy.

Keywords:
AUTODIRECTDIR uncertaintyStudent t distributiondeformable image registrationdose mapping error

More Related Videos

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation
10:33

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Published on: September 4, 2017

16.7K
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

1.6K

Related Experiment Videos

Last Updated: Mar 2, 2026

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.7K
Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation
10:33

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Published on: September 4, 2017

16.7K
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

1.6K

Area of Science:

  • Medical Imaging
  • Radiotherapy Physics
  • Computational Anatomy

Background:

  • Deformable image registration (DIR) is crucial for transferring radiation therapy dose calculations between CT images.
  • DIR algorithms are prone to mapping errors, impacting treatment accuracy.
  • An automated tool was developed to predict voxel-specific DIR dose mapping errors.

Purpose of the Study:

  • To extensively analyze and demonstrate the effectiveness of an automated deformable image registration evaluation of confidence (ADIR-EC) tool.
  • To assess ADIR-EC's capability in estimating dose mapping errors for DIR algorithms.
  • To validate ADIR-EC's performance across simulated and real patient data.

Main Methods:

  • Utilized 4 simulated patient deformations (3 B-spline, 1 rigid) to predict DIR algorithm uncertainty.
  • Validated the workflow with 2 DIR algorithms (Velocity, Plastimatch) on physical and virtual phantoms with known ground-truth.
  • Tested on 3 pairs of real patient lung images with identified landmarks.

Main Results:

  • Predicted Student t-distributions closely matched true dose mapping error distributions for both algorithms.
  • ADIR-EC confidence levels (50%, 68%, 95%) accurately encompassed actual errors (e.g., 48.8%, 66.3%, 93.8% for Velocity).
  • Error distributions from real patient data also aligned with predicted distributions, despite landmark sparsity.

Conclusions:

  • The automated deformable image registration evaluation of confidence tool effectively estimates dose mapping errors.
  • ADIR-EC provides accurate confidence intervals for dose-volume histograms in deformed dose calculations.
  • This tool enhances the reliability of deformable image registration in clinical applications.