phat 19(20): e8

Research Article

Algorithm to detect and calculate the cerebrospinal fluid (CSF) through Magnetic Resonance Imaging (MRI)

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  • @ARTICLE{10.4108/eai.13-7-2018.164179,
    author={Enrique Gonz\^{a}lez-Mart\^{\i}n and Guillermo Sosa-G\^{o}mez and Omar Rojas},
    title={Algorithm to detect and calculate the cerebrospinal fluid (CSF) through Magnetic Resonance Imaging (MRI)},
    journal={EAI Endorsed Transactions on Pervasive Health and Technology},
    volume={5},
    number={20},
    publisher={EAI},
    journal_a={PHAT},
    year={2019},
    month={11},
    keywords={Cerebrospinal Fluid (CSF), Magnetic Resonance Imaging, Image Registration, region growing},
    doi={10.4108/eai.13-7-2018.164179}
}
  • Enrique González-Martín
    Guillermo Sosa-Gómez
    Omar Rojas
    Year: 2019
    Algorithm to detect and calculate the cerebrospinal fluid (CSF) through Magnetic Resonance Imaging (MRI)
    PHAT
    EAI
    DOI: 10.4108/eai.13-7-2018.164179
Enrique González-Martín1, Guillermo Sosa-Gómez2, Omar Rojas2,*
  • 1: Universidad Central Marta Abreu de Las Villas, Santa Clara, Cuba
  • 2: Universidad Panamericana. Escuela de Ciencias Económicas y Empresariales. Álvaro del Portillo 49, Zapopan, Jalisco, 45010, México
*Contact email: orojas@up.edu.mx

Abstract

INTRODUCTION: An heuristic algorithm for detection and segmentation of cerebrospinal fluid through magnetic resonance imaging is presented.

OBJECTIVE: The objective of the method is to calculate the minimum amount of anesthesia to be used in patients at the time of an operation and thus make a decision based on the algorithm.

METHODS: The pattern-based CSF segmentation algorithm presented is based on finite cellular automata that takes as input light and dark images obtained from MRI methods.

RESULTS: Based on Fieldman’s test, results show that the algorithm is as efficient as the decision taken by two different operators regarding the mL of anesthesia to be used in the patient.

Keywords
Cerebrospinal Fluid (CSF), Magnetic Resonance Imaging, Image Registration, region growing
Received
2019-10-16
Accepted
2019-10-29
Published
2019-11-13
Publisher
EAI
http://dx.doi.org/10.4108/eai.13-7-2018.164179

Copyright © 2019 Enrique González-Martín et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.