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Related Experiment Video

Updated: Jun 6, 2026

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

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

Published on: April 14, 2014

MR CONTRAST SYNTHESIS FOR LESION SEGMENTATION.

Snehashis Roy¹, Aaron Carass, Navid Shiee

¹Image Analysis and Communications Laboratory, Electrical and Computer Engineering, The Johns Hopkins University.

Proceedings. IEEE International Symposium on Biomedical Imaging

|December 7, 2010

Summary

This summary is machine-generated.

This study introduces a novel method to generate synthetic magnetic resonance imaging (MRI) contrasts, specifically Fluid Attenuated Inversion Recovery (FLAIR) images, from existing T1 and T2 sequences. This technique enhances neuroimaging analysis by simulating alternative MRI contrasts without additional acquisition time.

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DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

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Published on: August 26, 2014

Area of Science:

Neuroimaging
Medical Image Analysis
Computational Neuroscience

Background:

Magnetic resonance (MR) contrast significantly impacts neuroimaging data utility for tasks like registration and segmentation.
Limited acquisition time often restricts obtaining multiple MR contrast images, hindering detailed analysis.

Purpose of the Study:

To develop an example-based approach for generating alternate MR contrast images from existing ones.
To simulate alternative pulse sequences, specifically generating Fluid Attenuated Inversion Recovery (FLAIR) images from T1 and T2 sequences.

Main Methods:

Utilizes patch matching from a multiple contrast atlas.
Applies an example-based approach to synthesize MR contrast images.
Focuses on generating synthetic FLAIR sequences from T1 and T2 pulse sequences.

Main Results:

Demonstrates the generation of synthetic FLAIR images from T1 and T2 sequences.
Shows the applicability of synthetic FLAIR for estimating white matter lesion segmentation.
Successfully simulates alternative MR contrasts, overcoming acquisition time limitations.

Conclusions:

The developed method effectively generates synthetic MR contrast images, enhancing neuroimaging data utility.
Synthetic FLAIR images are viable for downstream analysis tasks such as white matter lesion segmentation.
This approach offers a valuable tool for researchers facing constraints on MRI acquisition time.