Deep Learning Method for Estimation of Morphological Parameters Based on CT Scans

Rajarajeswari Ganesan; Antonino A. La Mattina; Frans N. Van De Vosse; Wouter Huberts

doi:10.3233/SHTI230142

Deep Learning Method for Estimation of Morphological Parameters Based on CT Scans

Rajarajeswari Ganesan^*, Antonino A. La Mattina, Frans N. Van De Vosse, Wouter Huberts

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

In this study, we propose a Convolutional Neural Network (CNN) with an assembly of non-linear fully connected layers for estimating body height and weight using a limited amount of data. This method can predict the parameters within acceptable clinical limits for most of the cases even when trained with limited data.

Original language	English
Title of host publication	Caring is Sharing - Exploiting the Value in Data for Health and Innovation
Subtitle of host publication	Proceedings of MIE 2023
Editors	Maria Hagglund, Madeleine Blusi, Stefano Bonacina, Lina Nilsson, Inge Cort Madsen, Sylvia Pelayo, Anne Moen, Arriel Benis, Lars Lindskold, Parisis Gallos
Publisher	IOS Press
Pages	364-365
Number of pages	2
Volume	302
Edition	1
ISBN (Electronic)	9781643683881
ISBN (Print)	9781643683881
DOIs	https://doi.org/10.3233/SHTI230142
Publication status	Published - 18 May 2023
Event	33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Swedish Exhibition & Congress Centre, Gothenburg, Sweden Duration: 22 May 2023 → 25 May 2023 Conference number: 33 https://www.mie2023.org/home-page

Publication series

Series	Studies in Health Technology and Informatics
Volume	302
ISSN	0926-9630

Conference

Conference	33rd Medical Informatics Europe Conference
Abbreviated title	MIE2023
Country/Territory	Sweden
City	Gothenburg
Period	22/05/23 → 25/05/23
Internet address	https://www.mie2023.org/home-page

Keywords

CNN
Deep Learning
Electronic Health Records (EHRs)
Height
Weight

Access to Document

10.3233/SHTI230142Licence: CC BY-NC

Cite this

Ganesan, R., La Mattina, A. A., Van De Vosse, F. N., & Huberts, W. (2023). Deep Learning Method for Estimation of Morphological Parameters Based on CT Scans. In M. Hagglund, M. Blusi, S. Bonacina, L. Nilsson, I. C. Madsen, S. Pelayo, A. Moen, A. Benis, L. Lindskold, & P. Gallos (Eds.), Caring is Sharing - Exploiting the Value in Data for Health and Innovation: Proceedings of MIE 2023 (1 ed., Vol. 302, pp. 364-365). IOS Press. https://doi.org/10.3233/SHTI230142

Ganesan, Rajarajeswari ; La Mattina, Antonino A. ; Van De Vosse, Frans N. et al. / Deep Learning Method for Estimation of Morphological Parameters Based on CT Scans. Caring is Sharing - Exploiting the Value in Data for Health and Innovation: Proceedings of MIE 2023. editor / Maria Hagglund ; Madeleine Blusi ; Stefano Bonacina ; Lina Nilsson ; Inge Cort Madsen ; Sylvia Pelayo ; Anne Moen ; Arriel Benis ; Lars Lindskold ; Parisis Gallos. Vol. 302 1. ed. IOS Press, 2023. pp. 364-365 (Studies in Health Technology and Informatics, Vol. 302).

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title = "Deep Learning Method for Estimation of Morphological Parameters Based on CT Scans",

abstract = "In this study, we propose a Convolutional Neural Network (CNN) with an assembly of non-linear fully connected layers for estimating body height and weight using a limited amount of data. This method can predict the parameters within acceptable clinical limits for most of the cases even when trained with limited data.",

keywords = "CNN, Deep Learning, Electronic Health Records (EHRs), Height, Weight",

author = "Rajarajeswari Ganesan and {La Mattina}, {Antonino A.} and {Van De Vosse}, {Frans N.} and Wouter Huberts",

note = "Funding Information: Acknowledgement: The authors acknowledge the EU funded project In Silico World, grant number 101016503. The dataset is available at http://doi.org/10.6092/unibo/ amsacta/7126 under the terms of the CC BY 4.0 International license. Publisher Copyright: {\textcopyright} 2023 European Federation for Medical Informatics (EFMI) and IOS Press.; 33rd Medical Informatics Europe Conference : Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023 ; Conference date: 22-05-2023 Through 25-05-2023",

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Ganesan, R, La Mattina, AA, Van De Vosse, FN & Huberts, W 2023, Deep Learning Method for Estimation of Morphological Parameters Based on CT Scans. in M Hagglund, M Blusi, S Bonacina, L Nilsson, IC Madsen, S Pelayo, A Moen, A Benis, L Lindskold & P Gallos (eds), Caring is Sharing - Exploiting the Value in Data for Health and Innovation: Proceedings of MIE 2023. 1 edn, vol. 302, IOS Press, Studies in Health Technology and Informatics, vol. 302, pp. 364-365, 33rd Medical Informatics Europe Conference, Gothenburg, Sweden, 22/05/23. https://doi.org/10.3233/SHTI230142

Deep Learning Method for Estimation of Morphological Parameters Based on CT Scans. / Ganesan, Rajarajeswari; La Mattina, Antonino A.; Van De Vosse, Frans N. et al.
Caring is Sharing - Exploiting the Value in Data for Health and Innovation: Proceedings of MIE 2023. ed. / Maria Hagglund; Madeleine Blusi; Stefano Bonacina; Lina Nilsson; Inge Cort Madsen; Sylvia Pelayo; Anne Moen; Arriel Benis; Lars Lindskold; Parisis Gallos. Vol. 302 1. ed. IOS Press, 2023. p. 364-365 (Studies in Health Technology and Informatics, Vol. 302).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

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DO - 10.3233/SHTI230142

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Ganesan R, La Mattina AA, Van De Vosse FN, Huberts W. Deep Learning Method for Estimation of Morphological Parameters Based on CT Scans. In Hagglund M, Blusi M, Bonacina S, Nilsson L, Madsen IC, Pelayo S, Moen A, Benis A, Lindskold L, Gallos P, editors, Caring is Sharing - Exploiting the Value in Data for Health and Innovation: Proceedings of MIE 2023. 1 ed. Vol. 302. IOS Press. 2023. p. 364-365. (Studies in Health Technology and Informatics, Vol. 302). doi: 10.3233/SHTI230142