Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Abdominal Aorta

Abdominal Aorta

Once the aorta traverses the diaphragmatic plane at the aortic hiatus, it is known as the abdominal aorta. This anatomical structure is positioned leftward of the spinal column, encased within a cocoon of adipose tissue behind the peritoneal cavity. It terminates at the L4 vertebra, where it splits into the common iliac arteries. Prior to this bifurcation, the abdominal aorta gives rise to several vital branches.
The celiac trunk, a singular artery, divides into the left gastric artery, which...

You might also read

Related Articles

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

Sort by

Same author

Analysis of Formimidoyltransferase Cyclodeaminase as a Potential Prognostic Biomarker and Therapeutic Target in Colorectal Cancer.

Cancer genomics & proteomics·2026

Same author

Deep learning-based artificial intelligence can improve the diagnosis of small bowel obstruction: stratified comparison study and hierarchical Bayesian model.

Scientific reports·2026

Same author

Endo-PairGS: pair priors for dynamic endoscopic scene reconstruction.

International journal of computer assisted radiology and surgery·2026

Same author

Endoscope-assisted single-port intragastric surgery for gastric submucosal tumors in the fornix.

Endoscopy·2026

Same author

Laparotomy After Total Pelvic Exenteration: Current Status and Techniques for Ileal Conduit Preservation.

Anticancer research·2026

Same author

Initial Experience with Three-Dimensional Holographic Virtual Bronchoscopy Using Mixed Reality for Peripheral Pulmonary Lesions: A Retrospective Feasibility Study.

Respiration; international review of thoracic diseases·2026

Search research articles

Related Experiment Video

Updated: Aug 24, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

A skeleton context-aware 3D fully convolutional network for abdominal artery segmentation.

Ruiyun Zhu¹, Masahiro Oda^2,3, Yuichiro Hayashi²

¹Graduate School of Informatics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi, Japan. rzhu@mori.m.is.nagoya-u.ac.jp.

International Journal of Computer Assisted Radiology and Surgery

|October 23, 2022

Summary

This study introduces a novel 3D deep learning network for precise abdominal artery segmentation from CT scans, improving accuracy for small vessels using skeleton context and a new patch generation method.

Keywords:

3D Fully convolutional network Abdominal artery segmentation CT image

More Related Videos

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Aug 24, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Published on: December 15, 2023

Area of Science:

Medical Imaging
Artificial Intelligence
Computer Vision

Background:

Accurate segmentation of abdominal arteries is crucial for diagnosis, treatment planning, and preoperative surgical guidance.
Existing deep learning methods struggle with segmenting small, complex vascular structures due to their intricate branching and positioning.
The challenge lies in capturing fine details and structural integrity of small blood vessels within medical imaging data.

Purpose of the Study:

To propose a novel 3D deep learning network for enhanced abdominal artery segmentation.
To improve the accuracy of segmenting small and complex abdominal blood vessels.
To introduce a skeleton context-aware approach and a new 3D patch generation technique for robust vascular segmentation.

Main Methods:

A 3D fully convolutional network (FCN) was developed for abdominal artery segmentation from CT volumes.
Two auxiliary tasks were integrated into the network to extract skeleton context information of the arteries.
A novel skeleton-based patch generation (SBPG) method was proposed to enhance training data diversity and improve segmentation of small arteries.

Main Results:

The proposed method demonstrated superior performance in segmenting abdominal arteries compared to existing techniques.
Experimental results on 20 abdominal CT volumes yielded an average precision of 95.5%, recall of 91.0%, and F-measure of 93.2%.
The method achieved a 1.5% improvement in average recall and a 0.7% improvement in average F-measure over a baseline method.

Conclusions:

A skeleton context-aware 3D FCN combined with a novel 3D patch generation method effectively segments abdominal arteries from CT volumes.
The fully automated approach successfully segmented most abdominal artery regions, demonstrating competitive performance.
The proposed deep learning framework offers a promising solution for accurate and efficient abdominal artery segmentation in clinical practice.