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Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Related Experiment Video

Updated: Jun 16, 2026

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

Published on: November 10, 2015

Enhancing Hippocampal Subfield Visualization Through Deep Learning Reconstructed MRI Scans.

Nikolaus Clodi¹, Benjamin Bender², Gretha Hecke¹

¹Department of Radiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria.

Diagnostics (Basel, Switzerland)

|June 26, 2025

Summary

Deep Resolve Boost (DRB) T2 TSE sequences are comparable to standard T2 TSE for hippocampal segmentation, offering reduced scan times without compromising diagnostic accuracy in epilepsy assessments.

Keywords:

FreeSurfer deep learning epilepsy hippocampus magnetic resonance tomography

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Last Updated: Jun 16, 2026

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Published on: November 10, 2015

A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures

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Published on: July 2, 2014

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

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Published on: April 14, 2014

Area of Science:

Neuroimaging
Radiology
Epilepsy Research

Background:

Assessing hippocampal pathology in epilepsy is crucial but challenging.
Deep learning reconstruction, standardized protocols, and advanced post-processing can improve diagnostic accuracy.
Evaluating novel MRI sequences for hippocampal volumetry is essential.

Purpose of the Study:

To compare T2 TSE Deep Resolve Boost (DRB) sequences with standard T2 TSE sequences for hippocampal segmentation and volumetry.
To assess the impact of DRB on image acquisition time and diagnostic accuracy.
To evaluate the utility of z-values for objective assessment of hippocampal pathology.

Main Methods:

FreeSurfer (v7.4.1) was used for hippocampal subregion segmentation in 36 subjects.
Comparison of volumes segmented from T2 TSE DRB and standard T2 TSE sequences.
Statistical analysis included two-tailed t-tests and z-values based on a 95% confidence interval.

Main Results:

Overall hippocampal volumes were identical between sequences.
Significant volume differences observed in specific right hippocampal subregions (CA1-Body, CA4-Body, whole hippocampal body) with low effect sizes.
DRB sequences reduced image acquisition time by 61% and identified pathological volume changes using z-scores.

Conclusions:

T2 TSE DRB sequences are non-inferior to conventional T2 TSE for hippocampal segmentation.
DRB enhances imaging efficiency while maintaining clinical reliability for epilepsy assessment.
The proposed 95% confidence interval aids objective evaluation of hippocampal pathology.