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Automatic torso detection in images of preterm infants
journal contribution
posted on 2023-05-19, 09:46 authored by Kaur, M, Andrew MarshallAndrew Marshall, Caillin Eastwood-SutherlandCaillin Eastwood-Sutherland, Brian SalmonBrian Salmon, Peter DargavillePeter Dargaville, Timothy GaleTimothy GaleImaging 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.
History
Publication title
Journal of Medical SystemsVolume
41Issue
9Article number
134Number
134ISSN
0148-5598Department/School
School of EngineeringPublisher
Kluwer Academic/Plenum PublPlace of publication
233 Spring St, New York, USA, Ny, 10013Rights statement
Copyright 2017 Springer Science+Business Media, LLCRepository Status
- Restricted