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Related Experiment Video

Updated: Jun 21, 2026

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

Accurate and robust brain image alignment using boundary-based registration.

Douglas N Greve1, Bruce Fischl

  • 1Martinos Center for Biomedical Imaging, 143 13th Street, Charlestown, MA, USA. greve@nmr.mgh.harvard.edu

Neuroimage
|July 4, 2009
PubMed
Summary
This summary is machine-generated.

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Boundary-Based Registration (BBR) is a novel algorithm for aligning brain images. It accurately registers partial or low-quality images, overcoming limitations of existing methods for neuroimaging analysis.

Area of Science:

  • Neuroimaging
  • Medical Image Analysis
  • Computational Neuroscience

Background:

  • Accurate brain image registration is crucial for analyzing neuroimaging data within and between subjects.
  • Existing registration algorithms struggle with fine spatial scales, strong intensity gradients, and partial brain images.

Purpose of the Study:

  • Introduce a new algorithm, Boundary-Based Registration (BBR), to improve the accuracy and robustness of brain image registration.
  • Address limitations of current methods in handling challenging imaging scenarios.

Main Methods:

  • BBR aligns input images to a high-resolution reference image by maximizing intensity gradients across tissue boundaries.
  • The reference image is used to extract surfaces separating tissue types.
  • Multiple lower-quality images can be registered by aligning them to the reference.

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Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities
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Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities

Published on: October 27, 2023

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Last Updated: Jun 21, 2026

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities
07:13

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities

Published on: October 27, 2023

Main Results:

  • BBR demonstrates superior accuracy and robustness compared to correlation ratio and normalized mutual information methods.
  • The algorithm effectively handles strong intensity inhomogeneities.
  • BBR excels at aligning partial-brain images to whole-brain images, a common failure point for other methods.

Conclusions:

  • Boundary-Based Registration (BBR) offers a more accurate and robust solution for human brain image registration.
  • BBR is particularly effective for challenging datasets, including partial-brain and low-quality images.
  • The method shows promise for enhancing within- and between-subject neuroimaging analysis.