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

You might also read

Related Articles

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

Sort by
Same author

Improving Cycle Life of Ni-Rich Li-Ion Battery Cathodes by Using Compartmentalized Anode and Cathode Electrolytes.

Small (Weinheim an der Bergstrasse, Germany)·2025
Same author

A Metastable Oxygen Redox Cathode for Lithium-Ion Batteries.

Angewandte Chemie (International ed. in English)·2025
Same author

The Role of Glutamine Synthetase on the Sensitivity to Radiotherapy of Hepatocellular Carcinoma.

Radiation research·2025
Same author

Semi-Confinement Effect Enhances CH<sub>4</sub> and C<sub>2</sub>H<sub>4</sub> Production in CO<sub>2</sub> Electrocatalytic Reduction.

Small (Weinheim an der Bergstrasse, Germany)·2025
Same author

Author Correction: A bioabsorbable mechanoelectric fiber as electrical stimulation suture.

Nature communications·2025
Same author

Association between visceral adiposity index and prostate cancer in men aged 40 years and older: a nationwide cross-sectional study.

The aging male : the official journal of the International Society for the Study of the Aging Male·2025

Related Experiment Video

Updated: May 3, 2026

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
11:38

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Published on: August 23, 2017

9.8K

Multi-atlas segmentation without registration: a supervoxel-based approach.

Hongzhi Wang1, Paul A Yushkevich1

  • 1Department of Radiology, University of Pennsylvania, USA.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|February 8, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a novel label transfer method for multi-atlas segmentation, improving accuracy for brain tumor segmentation by overcoming limitations of traditional techniques. The new approach enhances segmentation reliability for structures with variable locations.

More Related Videos

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

996
Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI&#8212;Application in Premanifest Huntington's Disease
09:06

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease

Published on: June 9, 2018

11.0K

Related Experiment Videos

Last Updated: May 3, 2026

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
11:38

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Published on: August 23, 2017

9.8K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

996
Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI&#8212;Application in Premanifest Huntington's Disease
09:06

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease

Published on: June 9, 2018

11.0K

Area of Science:

  • Medical image analysis
  • Computer vision
  • Computational anatomy

Background:

  • Multi-atlas segmentation relies on label transfer and fusion, typically assuming localized spatial support for structures.
  • This assumption limits its application in segmenting structures with high variability, such as brain tumors.
  • Existing methods struggle with reliable label transfer for brain tumor segmentation due to location variations.

Purpose of the Study:

  • To develop a novel label transfer technique for multi-atlas segmentation.
  • To address the limitations of current methods in segmenting structures with non-localized spatial support.
  • To improve the applicability of multi-atlas segmentation for brain tumor segmentation.

Main Methods:

  • Proposed a two-step label transfer technique inspired by Superparsing.
  • Oversegmented images into homogeneous regions (supervoxels).
  • Established voxel-wise correspondence by identifying similar supervoxels and then similar patches within those supervoxels.

Main Results:

  • Successfully applied the technique to brain tumor segmentation.
  • Demonstrated promising results, indicating improved segmentation accuracy.
  • Overcame the limitations of traditional multi-atlas segmentation for variable structures.

Conclusions:

  • The proposed label transfer technique enhances multi-atlas segmentation for challenging cases like brain tumors.
  • The supervoxel-based approach allows for more robust label transfer with non-localized structures.
  • This method shows potential for wider application in medical image segmentation.