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Brain Segmentation from Super-Resolved Magnetic Resonance Images

The objective of this work is to investigate the ability of a 2D super resolution (SR) technique in 3D restoration and enhancement of brain magnetic resonance images to facilitate the study of cerebral aging bio-markers. The SR method exploits the joint properties of the system point spread function...

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Main Authors:	Bazzi, Farah, Dios Rodriguez-Callejas, Juan D., Fonta, Caroline, Diab, Ahmad, Amoud, Hassan, Falou, Omar, Mescam, Muriel, Basarab, Adrian, Kouame, Denis
Format:	Conference Proceeding
Language:	English
Subjects:	Aging cerebral aging ICV Image segmentation Magnetic resonance imaging marmoset segmentation Single image super-resolution Spatial resolution structural MRI Three-dimensional displays Two dimensional displays
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creator	Bazzi, Farah Dios Rodriguez-Callejas, Juan D. Fonta, Caroline Diab, Ahmad Amoud, Hassan Falou, Omar Mescam, Muriel Basarab, Adrian Kouame, Denis
description	The objective of this work is to investigate the ability of a 2D super resolution (SR) technique in 3D restoration and enhancement of brain magnetic resonance images to facilitate the study of cerebral aging bio-markers. The SR method exploits the joint properties of the system point spread function and sub-sampling operators to derive a fast algorithm. Brain images of the common marmoset, Callithrix jacchus, acquired at different ages are used in this study. The evaluation of the final outcome of our method is done by computing the intracranial volume from the segmentation of the brain compartments: gray matter, white matter and cerebrospinal fluid. Results show that the deblurring of the images improves the segmentation process with respect to the ground truth. However, super resolution leads to the best quantification of the intracranial volume when compared to the deblurred and the original images. Therefore, despite its sub-optimality, the 2D SR method provides reliable results for improving the quality of the images used in the study of aging in terms of precision of reconstruction and computational time.
doi_str_mv	10.1109/ICABME47164.2019.8940281
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source	IEEE Xplore All Conference Series
subjects	Aging cerebral aging ICV Image segmentation Magnetic resonance imaging marmoset segmentation Single image super-resolution Spatial resolution structural MRI Three-dimensional displays Two dimensional displays
title	Brain Segmentation from Super-Resolved Magnetic Resonance Images
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