Clock Drawing Test Evaluation via Object Detection for Automatic Cognitive Impairment Diagnosis

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.