Hypoxic-ischaemic encephalopathy prognosis using susceptibility weighted image analysis based on histogram orientation gradient
Hypoxic-ischaemic encephalopathy prognosis using susceptibility weighted image analysis based on histogram orientation gradient
The aim of this study is to analyse the susceptibility-weighted magnetic resonance images (SWI) by using Histogram of Oriented Gradients (HOG) as a global feature to identify areas of the neonatal brain affected by Hypoxic-ischaemic encephalopathy (HIE). 42 infants with neonatal HIE have undergone under SW imaging in the neonatal period and have been investigated through neurodevelopmental assessment at 24 months of age. HOG features are used to represent the whole brain SW images and the region of interest separated from the brain image registration algorithm. We use k-nearest neighbours (kNN) and random forest to classify the SWI images into normal and abnormal groups, and then we compare our results to our previous work. The result shows an effective classification, which achieved an accuracy of 76.25±10.9. Our research suggests that automated analysis of neonatal SWI images can identify brain regions affected by HIE on SWI images and predict motor and cognitive outcomes.
Tang, Zhen
a8a50743-212f-4fb2-84f1-805f0758a83e
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Darekar, Angela
327a5432-d7d2-4ce6-ab2b-0d5db86298c3
Vollmer, Brigitte
044f8b55-ba36-4fb2-8e7e-756ab77653ba
Tang, Zhen
a8a50743-212f-4fb2-84f1-805f0758a83e
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Darekar, Angela
327a5432-d7d2-4ce6-ab2b-0d5db86298c3
Vollmer, Brigitte
044f8b55-ba36-4fb2-8e7e-756ab77653ba
Tang, Zhen, Mahmoodi, Sasan, Darekar, Angela and Vollmer, Brigitte
(2021)
Hypoxic-ischaemic encephalopathy prognosis using susceptibility weighted image analysis based on histogram orientation gradient.
In 15th International Joint Conference on Biomedical Engineering Systems and Technologies.
5 pp
.
(In Press)
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Conference or Workshop Item
(Paper)
Abstract
The aim of this study is to analyse the susceptibility-weighted magnetic resonance images (SWI) by using Histogram of Oriented Gradients (HOG) as a global feature to identify areas of the neonatal brain affected by Hypoxic-ischaemic encephalopathy (HIE). 42 infants with neonatal HIE have undergone under SW imaging in the neonatal period and have been investigated through neurodevelopmental assessment at 24 months of age. HOG features are used to represent the whole brain SW images and the region of interest separated from the brain image registration algorithm. We use k-nearest neighbours (kNN) and random forest to classify the SWI images into normal and abnormal groups, and then we compare our results to our previous work. The result shows an effective classification, which achieved an accuracy of 76.25±10.9. Our research suggests that automated analysis of neonatal SWI images can identify brain regions affected by HIE on SWI images and predict motor and cognitive outcomes.
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Accepted/In Press date: 8 December 2021
Venue - Dates:
15th International Joint Conference on Biomedical Engineering Systems and Technologies, , Vienna, Austria, 2022-02-09 - 2022-02-11
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Local EPrints ID: 453149
URI: http://eprints.soton.ac.uk/id/eprint/453149
PURE UUID: c8e79b2f-7c51-43dc-8ed1-057320b7cdfa
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Date deposited: 08 Jan 2022 22:40
Last modified: 27 Feb 2024 02:47
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Contributors
Author:
Zhen Tang
Author:
Sasan Mahmoodi
Author:
Angela Darekar
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