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Automatic Torso Detection in Images of Preterm Infants

  • Image & Signal Processing
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

Imaging systems have applications in patient respiratory monitoring but with limited application in neonatal intensive care units (NICU). In this paper we propose an algorithm to automatically detect the torso in an image of a preterm infant during non-invasive respiratory monitoring. The algorithm uses normalised cut to segment each image into clusters, followed by two fuzzy inference systems to detect the nappy and torso. Our dataset comprised overhead images of 16 preterm infants in a NICU, with uncontrolled illumination, and encompassing variations in poses, presence of medical equipment and clutter in the background. The algorithm successfully identified the torso region for 15 of the 16 images, with a high agreement between the detected torso and the torso identified by clinical experts.

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Author information

Authors and Affiliations

  1. School of Engineering and ICT, University of Tasmania, TAS, Hobart, 7001, Australia

    Meharmeet Kaur, Andrew P. Marshall, Caillin Eastwood-Sutherland, Brian P. Salmon & Timothy J. Gale

  2. Department of Paediatrics, Royal Hobart Hospital, TAS, Hobart, 7001, Australia

    Peter A. Dargaville

  3. Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia

    Peter A. Dargaville

Authors
  1. Meharmeet Kaur
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  2. Andrew P. Marshall
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  3. Caillin Eastwood-Sutherland
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  4. Brian P. Salmon
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  5. Peter A. Dargaville
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  6. Timothy J. Gale
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Corresponding author

Correspondence to Timothy J. Gale.

Ethics declarations

Conflict of interest

Meharmeet Kaur declares that she has no conflict of interest.

Andrew P. Marshall declares that he has no conflict of interest.

Caillin Eastwood-Sutherland declares that he has no conflict of interest.

Brian P. Salmon declares that he has no conflict of interest.

Peter A. Dargaville declares that he has no conflict of interest.

Timothy J. Gale declares that he has no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the University of Tasmania Human Research Ethics Committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from the parents of all individual participants included in the study.

Additional information

This article is part of the Topical Collection on Image & Signal Processing

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Kaur, M., Marshall, A.P., Eastwood-Sutherland, C. et al. Automatic Torso Detection in Images of Preterm Infants. J Med Syst 41, 134 (2017). https://doi.org/10.1007/s10916-017-0782-8

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  • DOI: https://doi.org/10.1007/s10916-017-0782-8

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