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

Ultrasound II: Endoscopic Ultrasound and FibroScan01:25

Ultrasound II: Endoscopic Ultrasound and FibroScan

950
Endoscopic Ultrasound (EUS) and FibroScan are valuable diagnostic tools in gastroenterology and hepatology, each with specific applications and techniques.
Endoscopic Ultrasound (EUS):
950
Imaging Studies II: Ultrasonography01:24

Imaging Studies II: Ultrasonography

645
IntroductionUltrasonography, or renal ultrasound, is a noninvasive medical imaging technique that uses high-frequency sound waves to visualize the kidneys, ureters, bladder, and surrounding tissues.Indications for Urinary System UltrasonographyUrinary system ultrasonography is indicated in various clinical scenarios, such as:Kidney Stones (Urolithiasis): To detect and monitor the size and presence of kidney or urinary tract stones.Hydronephrosis: To assess the dilation of the renal pelvis and...
645

You might also read

Related Articles

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

Sort by
Same author

Therapeutic potential of crystal-engineered berberine cocrystals ameliorates PCOS phenotypes via AMPK-IRS1/PI3K/Akt axis: An integrative computational and preclinical study.

The Journal of pharmacology and experimental therapeutics·2026
Same author

Modernizing Registry Operations: Implementing File*Pro Automation with Groovy Scripting to Streamline Data Processing in Missouri.

Journal of registry management·2026
Same author

A rare case of dual hormone-secreting pulmonary neuroendocrine tumor causing concurrent Cushing syndrome and acromegaly.

JCEM case reports·2026
Same author

Metabolic dysfunction-associated steatotic liver disease and bone mineral density in type 2 diabetes mellitus: insights from a single-center cross-sectional study in North India.

Frontiers in endocrinology·2026
Same author

Optineurin calibrates STING-mediated type I interferon response.

The FEBS journal·2026
Same author

Optimized Inductive Heating of a Superparamagnetic Zn<sub>x</sub>Mn<sub>1-x</sub>Fe<sub>2</sub>O<sub>4</sub> Hydrophilic Magneto-viscoelastic Fluid for Hyperthermia Application.

ACS applied bio materials·2025

Related Experiment Video

Updated: Mar 9, 2026

Imaging and Quantification of the Hepatic Vasculature of Mice Using Ultrafast Doppler Ultrasound
07:03

Imaging and Quantification of the Hepatic Vasculature of Mice Using Ultrafast Doppler Ultrasound

Published on: July 19, 2024

1.9K

Liver Ultrasound Image Segmentation Using Region-Difference Filters.

Nishant Jain1, Vinod Kumar2

  • 1Biomedical Laboratory, Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India. nishantjain86@gmail.com.

Journal of Digital Imaging
|December 28, 2016
PubMed
Summary

A novel region-difference filter method significantly improves liver ultrasound image segmentation accuracy and speed. This new approach outperforms existing methods, offering a more efficient tool for medical image analysis.

Keywords:
Active contour methodAlpha-trimmed filterAverage filterFuzzy C-meanImage processingImage segmentationLiverUltrasound imaging

More Related Videos

Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease
08:41

Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease

Published on: March 24, 2023

1.9K
Application of Ultrasound and Shear Wave Elastography Imaging in a Rat Model of NAFLD/NASH
07:13

Application of Ultrasound and Shear Wave Elastography Imaging in a Rat Model of NAFLD/NASH

Published on: April 20, 2021

4.6K

Related Experiment Videos

Last Updated: Mar 9, 2026

Imaging and Quantification of the Hepatic Vasculature of Mice Using Ultrafast Doppler Ultrasound
07:03

Imaging and Quantification of the Hepatic Vasculature of Mice Using Ultrafast Doppler Ultrasound

Published on: July 19, 2024

1.9K
Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease
08:41

Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease

Published on: March 24, 2023

1.9K
Application of Ultrasound and Shear Wave Elastography Imaging in a Rat Model of NAFLD/NASH
07:13

Application of Ultrasound and Shear Wave Elastography Imaging in a Rat Model of NAFLD/NASH

Published on: April 20, 2021

4.6K

Area of Science:

  • Medical Imaging
  • Image Processing
  • Computational Biology

Background:

  • Accurate segmentation of liver ultrasound (US) images is crucial for diagnosing and monitoring liver lesions.
  • Existing segmentation methods like Maximum A Posteriori-Markov Random Field (MAP-MRF), Chan-Vese Active Contour Method (CV-ACM), and Active Contour Region-Scalable Fitting Energy (RSFE) have limitations in accuracy and efficiency.
  • A need exists for improved segmentation techniques for liver US imaging.

Purpose of the Study:

  • To propose and evaluate a novel region-difference filter-based method for segmenting liver ultrasound images.
  • To compare the performance of the proposed method against established segmentation techniques (MAP-MRF, CV-ACM, RSFE).
  • To assess the accuracy and computational efficiency of the new segmentation approach.

Main Methods:

  • Region-difference filters were developed, evaluating the maximum difference of averages between two regions around a center pixel.
  • The filters were applied to generate a region-difference image, which was then binarized and morphologically processed for lesion segmentation.
  • The proposed method was implemented in MATLAB and compared with MAP-MRF, CV-ACM, and RSFE using liver US images from a clinical database and online resources.

Main Results:

  • A radiologist selected the proposed method's segmentation as best for 46 out of 56 test images.
  • The proposed method achieved an overall accuracy of 99.32%, significantly higher than MAP-MRF (85.9%), CV-ACM (98.71%), and RSFE (68.21%).
  • The proposed method demonstrated superior computational efficiency, with a processing time of 5.05 seconds compared to 26.44s (MAP-MRF), 24.82s (CV-ACM), and 28.36s (RSFE).

Conclusions:

  • The proposed region-difference filter method offers a highly accurate and efficient solution for liver ultrasound image segmentation.
  • This technique surpasses existing methods in both segmentation accuracy and processing speed.
  • The developed method holds significant potential for improving clinical diagnosis and management of liver conditions through enhanced medical image analysis.