Automated extraction of image segments from clinically diagnostic hand-drawn geometric shapes
Automated extraction of image segments from clinically diagnostic hand-drawn geometric shapes
Simple geometric shape drawing tasks are commonly used to diagnose and monitor patient performance for a range of clinical and neuropsychological conditions. Assessment relies upon observing the presence of components within a drawn image. Application of assessment criteria has been shown to vary amongst trained raters. An algorithm is presented to automatically extract the components from the static image of shape drawing responses. Specifically, images taken from a group of patients with visuo-spatial neglect and control subjects show the accurate identification of horizontal, vertical and diagonal components. Examples of performance metrics based on the features extracted from the component analysis show clear differences between neglect and control responses which are able to detect differences in performance more sensitive to the standard number of component assessment.
A440-A446
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Fairhurst, Michael
6a82d154-93fe-4657-bcee-934d5c888192
Potter, Jonathan
9f0adcdb-fe43-4c3b-b087-cd0d7ca687fc
6 August 2002
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Fairhurst, Michael
6a82d154-93fe-4657-bcee-934d5c888192
Potter, Jonathan
9f0adcdb-fe43-4c3b-b087-cd0d7ca687fc
Guest, Richard, Fairhurst, Michael and Potter, Jonathan
(2002)
Automated extraction of image segments from clinically diagnostic hand-drawn geometric shapes.
In,
Vajda, F.
(ed.)
Proceedings of the 26th Euromicro Conference.
26th Euromicro Conference (05/09/00 - 07/09/00)
IEEE, .
(doi:10.1109/EURMIC.2000.874527).
Record type:
Book Section
Abstract
Simple geometric shape drawing tasks are commonly used to diagnose and monitor patient performance for a range of clinical and neuropsychological conditions. Assessment relies upon observing the presence of components within a drawn image. Application of assessment criteria has been shown to vary amongst trained raters. An algorithm is presented to automatically extract the components from the static image of shape drawing responses. Specifically, images taken from a group of patients with visuo-spatial neglect and control subjects show the accurate identification of horizontal, vertical and diagonal components. Examples of performance metrics based on the features extracted from the component analysis show clear differences between neglect and control responses which are able to detect differences in performance more sensitive to the standard number of component assessment.
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More information
Published date: 6 August 2002
Venue - Dates:
26th Euromicro Conference, , Maastricht, Netherlands, 2000-09-05 - 2000-09-07
Identifiers
Local EPrints ID: 489585
URI: http://eprints.soton.ac.uk/id/eprint/489585
PURE UUID: 3d205fcf-76b6-4cf7-84e3-f9d5b79738cf
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Date deposited: 29 Apr 2024 16:35
Last modified: 30 Apr 2024 02:05
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Contributors
Author:
Richard Guest
Author:
Michael Fairhurst
Author:
Jonathan Potter
Editor:
F. Vajda
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