Presentation + Paper
4 April 2022 Errors of type or errors of degree? Cortical point targeting in transcranial magnetic stimulation
Author Affiliations +
Abstract
Transcranial magnetic stimulation is a non-invasive therapeutic procedure in which specific cortical brain regions are stimulated in order to disrupt abnormal neural behaviour. This procedure requires the annotation of a number of cortical point targets which is often performed by a human expert. Nevertheless, there is a large degree of variability between experts that cannot be described readily using the existing zero-mean uni-modal error model common in computer-assisted interventions. This is due to the error between experts arising from a difference of type rather than a difference of degree, that is, experts are not necessarily picking the same point with some error, but are picking fundamentally different points. In order to model these types of localisation errors, this paper proposes a simple probabilistic model that uses the agreement between annotations as a basis, not requiring a ground-truth annotation to be strictly known. This work will allow for the localisation error in transcranial magnetic stimulation to be better described which may spur further developments in clinical training as well as machine learning for cortical point localisation.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John S. H. Baxter, Stéphane Croci, Antoine Delmas, Luc Bredoux, Jean-Pascal Lefaucheur, and Pierre Jannin "Errors of type or errors of degree? Cortical point targeting in transcranial magnetic stimulation", Proc. SPIE 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, 1203403 (4 April 2022); https://doi.org/10.1117/12.2605797
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KEYWORDS
Computer simulations

Data modeling

Magnetic resonance imaging

3D image processing

Machine learning

Probability theory

Human-computer interaction

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