Computing geodesic paths on manifolds

Kimmel, Ron; Sethian, James A.

doi:10.1073/pnas.95.15.8431

Cited by 913 publications

(710 citation statements)

References 2 publications

(2 reference statements)

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“…More specifically, the projected positions of vertex points on the sphere are optimised so as to preserve the relative distances between points, as measured in the initial inflated mesh space. In each case, the distances (measured for the sphere and the input mesh) are estimated as geodesics, and are computed using a fast marching method for triangulated domains (Kimmel and Sethian, 1998). Note, the input mesh must first be scaled so that its surface area is equal to that of the unit sphere.…”

Section: Surface Inflation and Spherical Projectionmentioning

confidence: 99%

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

et al. 2018

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The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline * Corresponding author Email address: a.makropoulos11@imperial.ac.uk (Antonios Makropoulos) 1 These authors contributed equally Preprint submitted to NeuroImage January 7, 2018peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/125526 doi: bioRxiv preprint first posted online Apr. 10, 2017; consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

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Section: Surface Inflation and Spherical Projectionmentioning

confidence: 99%

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

et al. 2018

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“…Future implementation plans are directed toward the usage of maximum intensity projection technique (MIP) [21] that allows increasing the vessels tree visibility for the input dataset for the distance map creation. Do these results mean that the automatic planners planned better than the neurosurgeons?…”

Section: Discussionmentioning

confidence: 99%

Multi-trajectories automatic planner for StereoElectroEncephaloGraphy (SEEG)

et al. 2014

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Purpose StereoElectroEncephaloGraphy (SEEG) is done to identify the epileptogenic zone of the brain using several multi-lead electrodes whose positions in the brain are preoperatively defined. Intracranial hemorrhages due to disruption of blood vessels can cause major complications of this procedure (<1 %). In order to increase the intervention safety, we developed and tested planning tools to assist neurosurgeons in choosing the best trajectory configuration. Methods An automated planning method was developed that maximizes the distance of the electrode from the vessels and avoids the sulci as entry points. The angle of the guiding screws is optimized to reduce positioning error. The planner was quantitatively and qualitatively compared with manually computed trajectories on 26 electrodes planned for three patients undergoing SEEG by four neurosurgeons. Quantitative comparison was performed computing for each trajectory using (a) the Euclidean distance from the closest vessel and (b) the incidence angle. Results Quantitative evaluation shows that automatic planned trajectories are safer in terms of distance from the closest vessel with respect to manually planned trajectories. Qualitative evaluation performed by four neurosurgeons showed that the automatically computed trajectories would have been pre-E. De Momi (B) · C. Caborni · G. Ferrigno Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milan, Italy e-mail: elena.demomi@polimi.it

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“…The desired function T(x) is the time it takes to travel from Γ to x; because unit speed propagation is assumed, T is equivalent to geodesic distance. This equation can be solved using the fast marching (FM) method originally developed in Sethian (1996) and extended to triangulated domains in Kimmel and Sethian (1998).…”

Section: Geodesic Depth Calculationmentioning

confidence: 99%

Cortical surface segmentation and mapping

et al. 2004

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Segmentation and mapping of the human cerebral cortex from magnetic resonance (MR) images plays an important role in neuro-science and medicine. This paper describes a comprehensive approach for cortical reconstruction, flattening, and sulcal segmentation. Robustness to imaging artifacts and anatomical consistency are key achievements in an overall approach that is nearly fully automatic and computationally fast. Results demonstrating the application of this approach to a study of cortical thickness changes in aging are presented.

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Computing geodesic paths on manifolds

Cited by 913 publications

References 2 publications

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

Multi-trajectories automatic planner for StereoElectroEncephaloGraphy (SEEG)

Cortical surface segmentation and mapping

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