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

Range00:59

Range

14.4K
The range is one of the measures of variation. It can be defined as the difference between a dataset's highest and lowest values. For example, in the study of seven 16-ounce soda cans, the filled volume of soda was measured, thus producing the following amount (in ounces) of soda:
15.9; 16.1; 15.2; 14.8; 15.8; 15.9; 16.0; 15.5
Measurements of the amount of soda in a 16-ounce can vary since different subjects record these measurements or since the exact amount - 16 ounces of liquid, was not...
14.4K
¹H NMR: Long-Range Coupling01:27

¹H NMR: Long-Range Coupling

2.7K
The coupling interactions of nuclei across four or more bonds are usually weak, with J values less than 1 Hz. While these are usually not observed in spectra, the presence of multiple bonds along the coupling pathway can result in observable long-range coupling.
In alkenes, spin information is communicated via σ–π overlap, as seen in allylic (four-bond) and homoallylic (five-bond) couplings. These coupling interactions are stronger when the σ bond is parallel to the alkene...
2.7K
Ultrasound II: Endoscopic Ultrasound and FibroScan01:25

Ultrasound II: Endoscopic Ultrasound and FibroScan

733
Endoscopic Ultrasound (EUS) and FibroScan are valuable diagnostic tools in gastroenterology and hepatology, each with specific applications and techniques.
Endoscopic Ultrasound (EUS):
733
Variation: Normal Distribution, Range, and Standard Deviation02:32

Variation: Normal Distribution, Range, and Standard Deviation

28.7K
In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
28.7K
Angle of Twist - Elastic Range01:13

Angle of Twist - Elastic Range

830
Consider a cylindrical shaft with a length denoted by L and a consistent cross-sectional radius referred to as r. This shaft undergoes a torque at the free end. The highest shearing strain within the shaft is directly proportional to the twist angle and the radial distance from the shaft axis. When the shaft behaves elastically, this shearing strain can be articulated using variables such as the applied torque, radial distance, the polar moment of inertia, and the modulus of rigidity. By...
830
Range Rule of Thumb to Interpret Standard Deviation01:13

Range Rule of Thumb to Interpret Standard Deviation

13.7K
The range rule of thumb in statistics helps us calculate a dataset's minimum and maximum values with known standard deviation. This rule is based on the concept that 95% of all values in a dataset lie within two standard deviations from the mean.
For instance, the range rule of thumb can be used to find the tallest and the shortest student in a class, given the mean student height and standard deviation. If the mean student height is 1.6 m and the standard deviation, s is 0.05 m, the height...
13.7K

You might also read

Related Articles

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

Sort by
Same author

Sidewalk Hazard Detection Using a Variational Autoencoder and One-Class SVM.

Sensors (Basel, Switzerland)·2026
Same author

How reliable is robotic manipulation in the real world?

Science robotics·2025
Same author

Emergent patterns of interaction with dynamic objects.

PloS one·2025
Same author

The grand challenges of learning medical robot autonomy.

Science robotics·2025
Same author

Image-based simulation of mitral valve dynamic closure including anisotropy.

Medical image analysis·2024
Same author

Estimation of joint torque in dynamic activities using wearable A-mode ultrasound.

Nature communications·2024
Same journal

Correspondence-free local-to-global liver deformation correction via implicit neural representation and biomechanical model.

International journal of computer assisted radiology and surgery·2026
Same journal

BronchoLumen: analysis of recent YOLO-based architectures for real-time bronchial orifice detection in video bronchoscopy.

International journal of computer assisted radiology and surgery·2026
Same journal

Model-guided medicine for early diagnosis of transthyretin-associated cardiac amyloidosis using multimodal data integration and standardized interoperable models (the CRONOS-ATTR study).

International journal of computer assisted radiology and surgery·2026
Same journal

Electromagnetic navigation for femoral osteotomy using high-accuracy X-ray-to-CT registration.

International journal of computer assisted radiology and surgery·2026
Same journal

Modular instrument actuation unit for robotic-assisted systems in laparoscopic surgery.

International journal of computer assisted radiology and surgery·2026
Same journal

Pose-aware deep perceptual similarity for iterative 2D/3D registration of knee joints using contrastive learning.

International journal of computer assisted radiology and surgery·2026
See all related articles

Related Experiment Video

Updated: Feb 13, 2026

A Novel Application of Musculoskeletal Ultrasound Imaging
10:53

A Novel Application of Musculoskeletal Ultrasound Imaging

Published on: September 17, 2013

24.7K

High dynamic range ultrasound imaging.

Alperen Degirmenci1, Douglas P Perrin2,3, Robert D Howe4

  • 1School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA. adegirmenci@seas.harvard.edu.

International Journal of Computer Assisted Radiology and Surgery
|March 18, 2018
PubMed
Summary
This summary is machine-generated.

High dynamic range (HDR) ultrasound imaging enhances visualization of both bright and dark tissues in a single image. This technique improves diagnostic capabilities by revealing more tissue detail than conventional ultrasound.

Keywords:
Contrast enhancementHigh dynamic rangeImage enhancementTone mappingUltrasound imaging

More Related Videos

Point-of-Care Lung Ultrasound in Adults: Image Acquisition
09:17

Point-of-Care Lung Ultrasound in Adults: Image Acquisition

Published on: March 3, 2023

7.7K
Murine Echocardiography and Ultrasound Imaging
09:00

Murine Echocardiography and Ultrasound Imaging

Published on: August 8, 2010

37.4K

Related Experiment Videos

Last Updated: Feb 13, 2026

A Novel Application of Musculoskeletal Ultrasound Imaging
10:53

A Novel Application of Musculoskeletal Ultrasound Imaging

Published on: September 17, 2013

24.7K
Point-of-Care Lung Ultrasound in Adults: Image Acquisition
09:17

Point-of-Care Lung Ultrasound in Adults: Image Acquisition

Published on: March 3, 2023

7.7K
Murine Echocardiography and Ultrasound Imaging
09:00

Murine Echocardiography and Ultrasound Imaging

Published on: August 8, 2010

37.4K

Area of Science:

  • Medical Imaging
  • Computational Photography
  • Ultrasound Technology

Background:

  • High dynamic range (HDR) imaging enhances image quality by combining multiple exposures.
  • Ultrasound imaging has a limited dynamic range, hindering visualization of tissues with varying echogenicity.
  • Overexposure of hyperechogenic tissues and underexposure of hypoechogenic tissues are common limitations in ultrasound.

Purpose of the Study:

  • To apply HDR techniques to ultrasound imaging for improved visualization.
  • To combine ultrasound images acquired at different power levels to enhance detail.
  • To overcome the dynamic range limitations inherent in conventional ultrasound.

Main Methods:

  • Acquired ultrasound images of ex vivo and in vivo tissues at varying acoustic power levels.
  • Combined these images to create high dynamic range ultrasound (HDR-US) images.
  • Evaluated five tone mapping operators to identify the most effective for HDR-US.

Main Results:

  • HDR-US imaging successfully visualized both hyperechogenic and hypoechogenic tissues simultaneously.
  • The Durand tone mapping operator demonstrated superior detail preservation across the dynamic range.
  • Results were validated in both ex vivo and in vivo tissue samples.

Conclusions:

  • HDR-US imaging significantly enhances the visibility of tissue details.
  • This technique holds strong potential to improve ultrasound's utility in diagnosis and guidance.
  • The findings suggest a valuable advancement for medical imaging applications.