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

Probability Laws01:49

Probability Laws

43.9K
Overview
43.9K
Probability in Statistics01:14

Probability in Statistics

22.2K
Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
22.2K
Probability Histograms01:17

Probability Histograms

13.2K
A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
13.2K
Probability Distributions01:32

Probability Distributions

11.8K
 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
11.8K
Binomial Probability Distribution01:15

Binomial Probability Distribution

15.3K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
15.3K
Poisson Probability Distribution01:09

Poisson Probability Distribution

11.7K
A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
11.7K

You might also read

Related Articles

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

Sort by
Same author

A novel adaptive energy switching algorithm for proton arc therapy based on the machine-specific delivery characteristics.

Medical physics·2025
Same author

Brainstem catecholaminergic neurons induce torpor during fasting by orchestrating cardiovascular and thermoregulation changes.

Nature communications·2025
Same author

Feedforward inhibition of stress by brainstem neuropeptide Y neurons.

Nature communications·2024
Same author

Effect of erenumab on the reversion from chronic migraine to episodic migraine in an Asian population: A post hoc analysis of the DRAGON study.

Headache·2024
Same author

Characterization and Assessment of Sheep-Origin Probiotic Bacillus licheniformis B63 Strain for Potential Use in Intestinal Health and Disease.

Probiotics and antimicrobial proteins·2023
Same author

A phase 3, randomised, placebo-controlled study of erenumab for the prevention of chronic migraine in patients from Asia: the DRAGON study.

The journal of headache and pain·2022
Same journal

Amide proton transfer-weighted magnetic resonance imaging for predicting histopathology and biomarkers in rectal adenocarcinoma.

Quantitative imaging in medicine and surgery·2026
Same journal

Multimodality imaging for diagnosing and monitoring immunoglobulin G4-related coronary arteritis presenting as giant aneurysm: a case description.

Quantitative imaging in medicine and surgery·2026
Same journal

Investigation of the topological properties of brain structural and functional networks in patients with mild cognitive impairment.

Quantitative imaging in medicine and surgery·2026
Same journal

The critical role of transesophageal echocardiography in diagnosing carbon dioxide gas embolism: a case description and lessons learned.

Quantitative imaging in medicine and surgery·2026
Same journal

Impact of data augmentation size on deep learning-based third lumbar vertebra computed tomography skeletal muscle segmentation performance.

Quantitative imaging in medicine and surgery·2026
Same journal

Quantitative measurement of cutaneous neurofibromas in neurofibromatosis type 1 using a structured-light scanner.

Quantitative imaging in medicine and surgery·2026
See all related articles

Related Experiment Video

Updated: Jan 20, 2026

Robust 3D DNA FISH Using Directly Labeled Probes
12:16

Robust 3D DNA FISH Using Directly Labeled Probes

Published on: August 15, 2013

35.4K

Probability-based 3D k-space sorting for motion robust 4D-MRI.

Duohua Sun1, Xiao Liang2, Fangfang Yin1,2,3

  • 1Medical Physics Graduate Program, Duke Kunshan University, Kunshan 215316, China.

Quantitative Imaging in Medicine and Surgery
|August 27, 2019
PubMed
Summary
This summary is machine-generated.

A new probability-based sorting method significantly reduces motion artifacts in four-dimensional MRI (4D-MRI). This technique improves image quality and accuracy for radiation therapy guidance, especially for mobile targets.

Keywords:
4D-MRIMotion artifactsextended cardiac-torso (XCAT)k-space sortingprobability-based

More Related Videos

Author Spotlight: High-Resolution 4D Light-Sheet Imaging and Virtual Reality in Zebrafish for Single-Cell Analysis of Heart Function
07:07

Author Spotlight: High-Resolution 4D Light-Sheet Imaging and Virtual Reality in Zebrafish for Single-Cell Analysis of Heart Function

Published on: January 5, 2024

1.8K
A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates
08:41

A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates

Published on: July 17, 2020

5.3K

Related Experiment Videos

Last Updated: Jan 20, 2026

Robust 3D DNA FISH Using Directly Labeled Probes
12:16

Robust 3D DNA FISH Using Directly Labeled Probes

Published on: August 15, 2013

35.4K
Author Spotlight: High-Resolution 4D Light-Sheet Imaging and Virtual Reality in Zebrafish for Single-Cell Analysis of Heart Function
07:07

Author Spotlight: High-Resolution 4D Light-Sheet Imaging and Virtual Reality in Zebrafish for Single-Cell Analysis of Heart Function

Published on: January 5, 2024

1.8K
A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates
08:41

A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates

Published on: July 17, 2020

5.3K

Area of Science:

  • Medical Imaging
  • Radiotherapy
  • Image Reconstruction

Background:

  • Four-dimensional MRI (4D-MRI) is susceptible to motion artifacts caused by breathing variations.
  • These artifacts can compromise image quality and treatment accuracy.

Purpose of the Study:

  • To develop and evaluate a novel probability-based multi-cycle sorting method for motion-robust 4D-MRI.
  • To reduce breathing-variation-induced motion artifacts in 4D-MRI reconstruction.

Main Methods:

  • Extracted main breathing cycles from the respiratory signal.
  • Applied probability-based multi-cycle sorting to 3D k-space data for each cycle.
  • Compared the new method against conventional phase sorting using a 4D-extended cardiac-torso (XCAT) phantom and patient data.

Main Results:

  • Probability-based sorting demonstrated improved tumor-to-liver signal-to-noise ratio (SNR) and tumor volume consistency.
  • Achieved higher accuracy in average intensity projection (AIP) compared to phase sorting.
  • Significantly reduced motion artifacts in both simulated and real patient breathing data.

Conclusions:

  • Probability-based 3D k-space sorting is a feasible technique for motion-robust multi-cycle 4D-MRI.
  • This method effectively reduces motion artifacts, outperforming conventional sorting techniques.
  • The technique holds potential for enhancing the accuracy of radiation treatment guidance for mobile targets.