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 VII: Vascular Imaging01:19

Imaging Studies VII: Vascular Imaging

DefinitionRenal angiography, also known as renal arteriography, is an imaging technique used to obtain a comprehensive view of blood flow and the vascular structure of blood vessels in the kidneys and surrounding areas.PurposeRenal angiography detects blood vessel abnormalities in the kidneys, such as aneurysms, stenosis, thrombosis, vascular tumors, and renal artery stenosis. It evaluates kidney function and guides interventional treatments like angioplasty or stent placement.Pre-Procedure...
Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...

You might also read

Related Articles

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

Sort by
Same author

Emerged N193S mutation of PA-X protein disabled the immunity of mucosal dendritic cells for regulating virulence of clade 2.3.4.4b H5 subtype virus.

Emerging microbes & infections·2026
Same author

GSTM3 alleviates FLASH X-ray-induced testicular injury by modulating the ferroptosis pathway.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2026
Same author

Targeting programmed cell death in male infertility: pathogenic mechanisms and therapeutic strategies.

Molecular biology reports·2026
Same author

Real-world pharmacological treatment of patients with hyperemesis gravidarum in 9 cities of China from 2019 to 2024: a cross-sectional analysis.

Frontiers in pharmacology·2026
Same author

Intra-Arterial Alteplase After Successful Endovascular Reperfusion in Acute Stroke: The PEARL Randomized Clinical Trial.

JAMA·2026
Same author

Comment on "Association of Hospital For-profit Status with Clinical and Financial Outcomes Following Emergency General Surgery".

Surgery open science·2026

Related Experiment Video

Updated: Jul 10, 2026

Contrast Enhanced Vessel Imaging using MicroCT
05:50

Contrast Enhanced Vessel Imaging using MicroCT

Published on: January 27, 2011

Vascular-aware mixture-of-experts with a texture-enhanced decoder for accurate X-ray vessel segmentation.

Zhongjian Ju1,2,3, Qingnan Wu4, Wanqiang Cai1,2

  • 1Key Laboratory of New Generation Artificial Intelligence Technology and its Interdisciplinary Applications (Southeast University), Ministry of Education, Nanjing, Jiangsu, China.

BMC Medical Imaging
|July 9, 2026
PubMed
Summary
This summary is machine-generated.

A new Vascular-Aware Mixture-of-Experts (VA-MoE) framework improves X-ray angiography (XRA) vessel segmentation by enhancing structural modeling and texture recovery. This method shows promise for automated cardiovascular image analysis and disease diagnosis.

Keywords:
Mixture-of-expertsTexture enhancementVessel segmentationX-ray angiography

More Related Videos

A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage
08:12

A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage

Published on: July 28, 2018

A Full Skin Defect Model to Evaluate Vascularization of Biomaterials In Vivo
07:56

A Full Skin Defect Model to Evaluate Vascularization of Biomaterials In Vivo

Published on: August 28, 2014

Related Experiment Videos

Last Updated: Jul 10, 2026

Contrast Enhanced Vessel Imaging using MicroCT
05:50

Contrast Enhanced Vessel Imaging using MicroCT

Published on: January 27, 2011

A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage
08:12

A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage

Published on: July 28, 2018

A Full Skin Defect Model to Evaluate Vascularization of Biomaterials In Vivo
07:56

A Full Skin Defect Model to Evaluate Vascularization of Biomaterials In Vivo

Published on: August 28, 2014

Area of Science:

  • Medical imaging analysis
  • Computer-aided diagnosis
  • Cardiovascular imaging

Background:

  • Accurate vessel segmentation in X-ray angiography (XRA) is critical for diagnosing coronary artery disease and guiding interventions.
  • Challenges include low contrast, complex backgrounds, and variations in vessel size, particularly affecting thin vessels.

Purpose of the Study:

  • To develop and evaluate a novel framework for enhanced XRA vessel segmentation.
  • To address the limitations of existing methods in accurately segmenting challenging vascular structures.

Main Methods:

  • Proposed a Vascular-Aware Mixture-of-Experts (VA-MoE) framework.
  • Incorporated Dynamic Snake Convolution (DSnC) for vessel morphology and a Texture-Enhanced Decoder (TED) for detail recovery.
  • Evaluated on ARCADE, DCA1, and XCAD datasets.

Main Results:

  • VA-MoE achieved high performance: IoU of 87.80% and Dice of 93.08% on ARCADE; IoU of 65.18% and Dice of 78.03% on DCA1; IoU of 67.52% and Dice of 79.93% on XCAD.
  • Demonstrated superior performance over baseline methods, with notable improvements in IoU and Dice coefficients.
  • Qualitative analysis indicated enhanced topological continuity and better preservation of thin vessels.

Conclusions:

  • The VA-MoE framework offers a robust solution for XRA vessel segmentation.
  • Jointly enhancing vascular structure and texture recovery supports automated cardiovascular image analysis.