Automated parcellation of the brain surface generated from magnetic resonance images

✓ Data from single 10-minute magnetic resonance scans were used to create three-dimensional (3-D) views of the surfaces of the brain and skin of 12 patients. In each case, these views were used to make a preoperative assessment of the relationship of lesions to brain surface structures associated with movement, sensation, hearing, and speech. Interactive software was written so that the user could “slice” through the 3-D computer model and inspect cross-sectional images at any level. A surgery simulation program was written so that surgeons were able to “rehearse” craniotomies on 3-D computer models before performing the actual operations. In each case, the qualitative accuracy of the 3-D views was confirmed by intraoperative inspection of the brain surface and by intraoperative electrophysiological mapping, when available.

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Fast Nonsupervised 3D Registration of PET and MR Images of the Brain

Journal of Cerebral Blood Flow & Metabolism ◽

10.1038/jcbfm.1994.96 ◽

1994 ◽

Vol 14 (5) ◽

pp. 749-762 ◽

Cited By ~ 66

Author(s):

Jean-François Mangin ◽

Vincent Frouin ◽

Isabelle Bloch ◽

Bernard Bendriem ◽

Jaime Lopez-Krahe

Keyword(s):

Three Dimensional ◽

Magnetic Resonance Images ◽

Surface Matching ◽

3D Registration ◽

Matching Algorithm ◽

Distance Map ◽

Brain Surface ◽

Discrete Surfaces ◽

Positron Emission ◽

The Brain

We propose a fully nonsupervised methodology dedicated to the fast registration of positron emission tomography (PET) and magnetic resonance images of the brain. First, discrete representations of the surfaces of interest (head or brain surface) are automatically extracted from both images. Then, a shape-independent surface-matching algorithm gives a rigid body transformation, which allows the transfer of information between both modalities. A three-dimensional (3D) extension of the chamfer-matching principle makes up the core of this surface-matching algorithm. The optimal transformation is inferred from the minimization of a quadratic generalized distance between discrete surfaces, taking into account between-modality differences in the localization of the segmented surfaces. The minimization process is efficiently performed via the precomputation of a 3D distance map. Validation studies using a dedicated brain-shaped phantom have shown that the maximum registration error was of the order of the PET pixel size (2 mm) for the wide variety of tested configurations. The software is routinely used today in a clinical context by the physicians of the Service Hospitalier Frédéric Joliot (>150 registrations performed). The entire registration process requires ∼5 min on a conventional workstation.

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Ensemble learning-based classification on local patches from magnetic resonance images to detect iron depositions in the brain

International Journal of Bio-Inspired Computation ◽

10.1504/ijbic.2021.10039664 ◽

2021 ◽

Vol 17 (4) ◽

pp. 260

Author(s):

Beshiba Wilson ◽

Ruma Madhu Sreedharan ◽

Julia Punitha Malar Dhas ◽

Ram P. Krish

Keyword(s):

Magnetic Resonance ◽

Ensemble Learning ◽

Magnetic Resonance Images ◽

The Brain

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Spatially Localized Magnetic Resonance Spectroscopy of the Brains of Normal and Asphyxiated Newborns

PEDIATRICS ◽

10.1542/peds.87.3.273 ◽

1991 ◽

Vol 87 (3) ◽

pp. 273-282

Author(s):

J. Moorcraft ◽

N. M. Bolas ◽

N. K. Ives ◽

P. Sutton ◽

M. J. Blackledge ◽

...

Keyword(s):

Magnetic Resonance ◽

Magnetic Resonance Spectroscopy ◽

Brain Tissue ◽

Neurodevelopmental Outcome ◽

Birth Asphyxia ◽

Resonance Spectroscopy ◽

Rotating Frame ◽

Metabolic Derangement ◽

Brain Surface ◽

The Brain

Phase-modulated rotating frame imaging is a modification of magnetic resonance spectroscopy, which uses a linear radiofrequency field gradient to obtain spatially localized biochemical information. Phase-modulated rotating frame imaging was used to study regional cerebral energy metabolism in the brains of 9 normal newborns and 25 newborns after birth asphyxia. Relative concentrations of phosphorus-containing metabolites and intracellular pH were determined for brain tissue at three specified depths below the brain surface for all neonates. Wide variations in metabolite ratios were seen among normal neonates, and considerable metabolic heterogeneity was demonstrated in individual neonates by depth-resolved spectroscopy. Asphyxiated neonates with severe hypoxic-ischemic encephalopathy and a poor neurodevelopmental outcome showed the expected rise in inorganic orthophosphate and fall in phosphocreatine concentrations in both global and spatially localized spectra. Phase-modulated rotating frame imaging showed that metabolic derangement was less in superficial than in deeper brain tissue. The inorganic orthophosphateadenosine triphosphate ratio from 1 to 2 cm below the brain surface was more accurate than any global metabolite ratio for the identification of neonates with a poor short-term outcome. These data are consistent with the known vulnerability of subcortical brain tissue to hypoxic-ischemic injury in the full-term neonate.

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