|Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3287|
This paper describes an a novel surgical ontology based approach with haptics for neurosurgical operations. The work describes a detailed segmentation of various sulcal and gyral areas for the cortical surface and some interesting mesh generation approaches in defining various folds
and surface characteristics.
The work then helps to intrepret definition of a mesh based surface through precise monitoring and control for definition of underlying surgical ontology thereby giving the clinician control over neurosurgical simulation and operating procedure. The kind of impact and processing is at high granularity in terms of mesh definition and refinement.
The authors present building blocks in creating a neurosurgical pipeline and framework by which you can alter the decision making process with sufficient geometric and information centric knowledge
of the system developed.Hypothesis:
The authors make few assumptions regarding coarseness of meshes that can be generated, principally, one assumes that such a mesh will exist and sufficient resolution and can be recreated from MR scans.
One fundamental assumption that shines through is that there is indeed a need for a flexible approach towards information centric decision making for neurosurgical procedures and this I believe is from existing reference literature and retrospectice studies.Evidence:
The evidence is from finite element simulations of the surgical process using the SOFA framework which helps present a mesh based deformation approach to surgical simulation.
Snapshots in 3.4 illustrate some components of such as a decision support system and neurosurgical pipeline based approach to perform surgery and is in the right direction towards providing
evidence for the use of this kind of idea for surgical simulation. More use cases or clinical examples would be valuable.
The authors definitely have evidence for a pedantic system for neurosurgical mesh processing and surgical preordering with the system proposed.Open Science:
I dont there is supporting code as part of this paper submission. The code and data might be part of an earlier software build that I'd have to find and compile to provide comments for this section.
Enough details are not provided currently but might available as part of this submission through an earlier release.Reproducibility:
No I havent downloaded or compiled the code. I'd like to to be able to review mesh refinement quality and neuro pipeline generation since this seems like an important information centric framework to adopt and use.Quality of the data :
There is no data on the paper review system that might be part of an earlier build so I cant comment on these topics.Interest:
This work has immense benefit in the MR elastography world for computational simulation.
Other areas are orthopedic soft tissue simulation, similar pipeline utility generation and solution of ODE's towards solving some complex biological problems.
Interestingly enough, there is scope for collaboration and simulation from a haptics standpoint that would be of great value in the clinical OR world.Free comment :
This paper provides a novel surgical ontological approach and has critical components of biomedical processing such as computation, mesh refinement and creation of an decision support framework.
Of interesting clinical value that might be applicable in a neurorehabilitation environment. I can lend my clinical engineering ideas and expertise for further development if needed.
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|Categories:||Atlas-based segmentation, Mesh|
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