Tractography Methods in Preoperative Neurosurgical Planning

Authors

  • Mateusz Koryciński
  • Konrad A. Ciecierski

DOI:

https://doi.org/10.26636/jtit.2021.154521

Keywords:

artificial intelligence, diffusion tensor imaging, Dijkstra’s algorithm, graph traversing, MRI, neural networks, tractography

Abstract

Knowledge of the location of nerve tracts during the surgical preoperative planning stage and during the surgery itself may help neurosurgeons limit the risk of causing neurological deficits affecting the patient’s essential abilities. Development of MRI techniques has helped profoundly with in vivo visualization of the brain’s anatomy, enabling to obtain images within minutes. Different methodologies are relied upon to identify anatomical or functional details and to determine the movement of water molecules, thus allowing to track nerve fibers. However, precise determination of their location continues to be a labor-intensive task that requires the participation of highly-trained medical experts. With the development of computational methods, machine learning and artificial intelligence, many approaches have been proposed to automate and streamline that process, consequently facilitating image-based diagnostics. This paper reviews these methods focusing on their potential use in neurosurgery for better planning and intraoperative navigation.

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Published

2021-09-30

Issue

Section

ARTICLES FROM THIS ISSUE

How to Cite

[1]
M. Koryciński and K. A. Ciecierski, “Tractography Methods in Preoperative Neurosurgical Planning”, JTIT, vol. 85, no. 3, pp. 78–85, Sep. 2021, doi: 10.26636/jtit.2021.154521.