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Imaging Studies I: CT and MRI

Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
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Imaging Studies III: Computed Tomography01:27

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Related Experiment Video

Updated: Jun 26, 2026

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Published on: July 1, 2014

Simultaneous confidence regions for image excursion sets: A validation study with applications in fMRI.

Jiyue Qin1, Samuel Davenport1, Armin Schwartzman1,2

  • 1Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, CA, United States.

Imaging Neuroscience (Cambridge, Mass.)
|June 25, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for simultaneous confidence regions (SCRs) in functional Magnetic Resonance Imaging (fMRI) analysis. This approach works for all activation thresholds and brain data types, improving brain activation localization.

Keywords:
bootstrapfMRIsimultaneous confidence bandsimultaneous confidence regions

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Published on: June 30, 2018

Area of Science:

  • Neuroimaging
  • Statistical analysis
  • Brain mapping

Background:

  • Functional Magnetic Resonance Imaging (fMRI) is crucial for localizing brain activity during tasks.
  • Existing methods for confidence regions in fMRI are limited to single thresholds and brain volumes, neglecting cortical surface analyses.
  • There is a need for more flexible and sensitive statistical approaches in fMRI data analysis.

Purpose of the Study:

  • To develop and validate a novel approach for constructing simultaneous confidence regions (SCRs) applicable to all activation thresholds.
  • To extend existing SCR methods to handle both brain volume and cortical surface data in fMRI studies.
  • To evaluate the performance of different bootstrap variants for fMRI data analysis.

Main Methods:

  • The study adapts a bootstrap-based method for constructing simultaneous confidence bands (SCBs) to fMRI data.
  • Extensive 2D simulations were performed to assess the validity of various bootstrap methods, including nonparametric and multiplier bootstrap variants.
  • Realistic noise simulations using resampled resting-state 3D fMRI data were employed for further validation.

Main Results:

  • The Rademacher multiplier bootstrap-t demonstrated superior performance, achieving near-nominal coverage rates even with small sample sizes (n=10).
  • The proposed SCR approach is valid across all activation thresholds and applicable to both volumetric and surface-based fMRI data.
  • The implementation supports multi-dimensional data and includes interactive visualization tools for fMRI analysis.

Conclusions:

  • The developed SCR method offers a robust and versatile tool for statistical inference in fMRI studies.
  • This approach enhances the sensitivity and applicability of brain activation localization compared to traditional methods.
  • The method is validated for both simulated and real-world fMRI data, including Human Connectome Project datasets.