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 Experiment Videos

Shape-based averaging.

Torsten Rohlfing1, Calvin R Maurer

  • 1SRI International, Menlo Park, CA 94025-3493, USA. torsten@synapse.sri.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 8, 2007
PubMed
Summary
This summary is machine-generated.

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

The natverse, a versatile toolbox for combining and analysing neuroanatomical data.

eLife·2020
Same author

Influences of Age, Sex, and Moderate Alcohol Drinking on the Intrinsic Functional Architecture of Adolescent Brains.

Cerebral cortex (New York, N.Y. : 1991)·2017
Same author

Concomitants of alcoholism: differential effects of thiamine deficiency, liver damage, and food deprivation on the rat brain in vivo.

Psychopharmacology·2016
Same author

Brain metabolite levels in recently sober individuals with alcohol use disorder: Relation to drinking variables and relapse.

Psychiatry research. Neuroimaging·2016
Same author

Harmonizing DTI measurements across scanners to examine the development of white matter microstructure in 803 adolescents of the NCANDA study.

NeuroImage·2016
Same author

Cognitive, emotion control, and motor performance of adolescents in the NCANDA study: Contributions from alcohol consumption, age, sex, ethnicity, and family history of addiction.

Neuropsychology·2016
Same journal

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

GoP-based Quality Enhancement on Video Compression.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Align then Tensorize: Multi-Level Consistent Anchor Graph Learning for Scalable Multi-View Clustering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Beyond Fidelity: Diverse Image Synthesis via Retrieval-Augmented Diffusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

A new shape-based averaging (SBA) method improves image segmentation by creating more contiguous and accurate results. This technique is particularly effective for non-numerical data like brain MRIs, outperforming label voting in several aspects.

Area of Science:

  • Medical Imaging
  • Computer Vision
  • Image Processing

Background:

  • Averaging multidimensional images is crucial for tasks like segmentation analysis.
  • Existing methods may introduce artifacts or struggle with non-numerical data.

Purpose of the Study:

  • To introduce a novel shape-based averaging (SBA) algorithm for multidimensional images.
  • To evaluate SBA's performance against label voting for averaging image segmentations.

Main Methods:

  • The shape-based averaging (SBA) method utilizes signed Euclidean distance maps.
  • SBA was applied to segmented human brain MRI data.
  • Performance was compared to label voting in a multiclassifier setting.

Main Results:

Related Experiment Videos

  • Shape-based averaging (SBA) achieved comparable recognition rates to label voting.
  • SBA produced segmentations with improved contiguity and reduced fragmentation.
  • SBA demonstrated robustness with fewer atlases and lower resolutions, especially with shape-based interpolation.

Conclusions:

  • Shape-based averaging (SBA) enhances the contiguity and accuracy of averaged image segmentations.
  • SBA is suitable for non-numerical data and offers advantages over label voting for segmentation tasks.