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

Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

429
Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
429
Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

Radiological Investigation II: MRI and Ventilation Perfusion Scan

699
Description
Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
MRI
MRI uses magnetic fields and radiofrequency signals to distinguish between normal and abnormal tissues. This technology provides a more detailed diagnostic image than CT scans, enabling it to characterize pulmonary nodules, stage bronchogenic carcinoma, and evaluate inflammatory activity in...
699

You might also read

Related Articles

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

Sort by
Same author

Duplication of 4-bp in SACS leads to autosomal recessive spastic ataxia of Charlevoix-Saguenay type in two Pakistani patients.

Human genome variation·2026
Same author

Negative Appendectomy Rates and Their Correlation With the Use of Histopathology: A Clinical Audit.

Cureus·2026
Same author

Early-Onset Retinopathy in Patients With Variants in SLC6A6 Leading to Impaired Taurine Transport.

JAMA ophthalmology·2025
Same author

A novel homozygous DST variant causes hereditary sensory and autonomic neuropathy in a Pakistani family.

Human genome variation·2025
Same author

Artificial intelligence for diagnosis and prognosis of thymic epithelial tumors: a systematic review.

Mediastinum (Hong Kong, China)·2025
Same author

Vision transformer and Mamba-attention fusion for high-precision PCB defect detection.

PloS one·2025

Related Experiment Video

Updated: Feb 22, 2026

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

43.6K

Segmentation of Left and Right Ventricles in Cardiac MRI Using Active Contours.

Shafiullah Soomro1, Farhan Akram2, Asad Munir1

  • 1Department of Computer Science and Engineering, Chung-Ang University, Seoul 156-756, Republic of Korea.

Computational and Mathematical Methods in Medicine
|September 21, 2017
PubMed
Summary

This study introduces a novel hybrid signed pressure force function for improved cardiac magnetic resonance imaging (MRI) segmentation. The method accurately delineates heart ventricles, overcoming common image challenges for better diagnostic analysis.

More Related Videos

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse
15:26

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse

Published on: May 19, 2015

14.9K
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
08:10

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

Published on: July 20, 2022

2.2K

Related Experiment Videos

Last Updated: Feb 22, 2026

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

43.6K
3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse
15:26

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse

Published on: May 19, 2015

14.9K
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
08:10

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

Published on: July 20, 2022

2.2K

Area of Science:

  • Medical Imaging
  • Image Segmentation
  • Cardiovascular Analysis

Background:

  • Accurate segmentation of cardiac ventricles in MRI is essential for quantitative analysis.
  • Intensity inhomogeneity and blurred boundaries in cardiac MRI hinder traditional segmentation methods.
  • Existing intensity-based segmentation techniques struggle with precise delineation of regions of interest (ROI).

Purpose of the Study:

  • To develop an advanced segmentation method for cardiac MRI.
  • To address challenges of intensity inhomogeneity and blurred boundaries in ventricle segmentation.
  • To improve the accuracy and robustness of cardiac MRI segmentation.

Main Methods:

  • A hybrid signed pressure force function (SPF) was developed, integrating local and global image fitting.
  • A characteristic term was incorporated into the SPF to constrain contours within the ROI.
  • Quantitative validation was performed using overlapping Dice index and Hausdorff-Distance metrics on cardiac datasets.

Main Results:

  • The proposed method achieved high Dice Similarity Coefficient (DSC) values: 0.95 (endocardial) and 0.97 (epicardial) on the 2009 LV MICCAI dataset.
  • On the 2012 RV MICCAI dataset, endocardial segmentation yielded DSC values of 0.97 (ED) and 0.90 (ES), with HD values of 8.51 and 7.67.
  • Epicardial segmentation on the 2012 RV MICCAI dataset achieved DSC values of 0.92 (ED) and 0.91 (ES), with HD values of 6.47 and 9.34.

Conclusions:

  • The proposed hybrid SPF method demonstrates robust performance in cardiac MRI segmentation.
  • The technique effectively overcomes intensity inhomogeneity and boundary delineation issues.
  • This advanced segmentation approach offers significant potential for quantitative cardiac MRI analysis.