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Clock Drawing Test Evaluation via Object Detection for Automatic Cognitive Impairment Diagnosis
- Source :
- 2020 IEEE 6th International Conference on Computer and Communications (ICCC).
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- Dementia refers to a group of syndromes with cognitive impairment as the main clinical manifestation. Amongst various neuropsychological tests for clinical diagnosis of dementia, the clock drawing test (CDT) is frequently used due to its simplicity and effectiveness. In order to extricate physicians from their involvement in CDT scoring, we propose an automatic scoring method via object detection for accurate and efficient dementia screening. Given the drawn clock picture by a testee, this end-to-end method for CDT scoring directly produces the final score without any human interventions. Moreover, the proposed method can handle two ways of data acquisition scanned data set which contains the scanned version of drawn clocks and camera data set which consists of the drawn clocks taken from normal cameras. Extensive experimental results demonstrate the validity and feasibility of the proposed method. Specifically, the precision of the scanned dataset scored by a seven-point method and the camera dataset by a three-point method is 94.64% and 92.36% respectively, while that of junior outpatient physicians is 92.03% within the camera dataset.
- Subjects :
- Artificial neural network
business.industry
Computer science
Deep learning
Neuropsychology
Pattern recognition
02 engineering and technology
010501 environmental sciences
medicine.disease
01 natural sciences
Object detection
Data set
Data acquisition
0202 electrical engineering, electronic engineering, information engineering
medicine
Dementia
020201 artificial intelligence & image processing
Artificial intelligence
business
Cognitive impairment
Clock drawing test
0105 earth and related environmental sciences
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 IEEE 6th International Conference on Computer and Communications (ICCC)
- Accession number :
- edsair.doi...........4300dfb5c9561763537488af6e357b65
- Full Text :
- https://doi.org/10.1109/iccc51575.2020.9345030