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Related Concept Videos

Multiple Comparison Tests01:13

Multiple Comparison Tests

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Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
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IR Frequency Region: Fingerprint Region01:03

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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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Related Experiment Video

Updated: Mar 7, 2026

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
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Algorithm comparison for schedule optimization in MR fingerprinting.

Ouri Cohen1, Matthew S Rosen2

  • 1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA; Department of Radiology, Harvard Medical School, Boston, MA 02115, USA.

Magnetic Resonance Imaging
|February 28, 2017
PubMed
Summary
This summary is machine-generated.

Optimizing magnetic resonance fingerprinting (MRF) acquisition schedules improves tissue differentiation and reduces scan times. This study evaluates various optimization algorithms to find the most effective method for MRF schedule optimization.

Keywords:
MR fingerprintingMRFSchedule optimizationTissue discrimination

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Area of Science:

  • Medical Imaging
  • Biophysics
  • Computational Science

Background:

  • Magnetic Resonance Fingerprinting (MRF) uses pseudorandom schedules for flip angles and repetition times.
  • Previous research demonstrated that optimizing MRF acquisition schedules enhances tissue discrimination and reduces required measurements.

Purpose of the Study:

  • To identify the optimal algorithm for enhancing MRF acquisition schedule design.
  • To compare the efficacy of different optimization algorithms in the context of MRF.

Main Methods:

  • Evaluation of several distinct optimization algorithms.
  • Application of algorithms to optimize MRF acquisition schedules for improved tissue characterization.

Main Results:

  • Comparative analysis of algorithm performance in optimizing MRF schedules.
  • Identification of algorithms that best maximize tissue discrimination.

Conclusions:

  • The selection of an appropriate optimization algorithm is critical for efficient MRF.
  • Optimized schedules derived from superior algorithms can lead to faster and more accurate MRF scans.