A Real-time Image Analysis System for Computer-Assisted Diagnosis of Neurological Disorders

✍ Scribed by Teewoon Tan; Ling Guan; John Burne

• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 861 KB
• Volume: 5
• Category: Article
• ISSN: 1077-2014
• DOI: 10.1006/rtim.1998.0139

✦ Synopsis

his paper describes the application of digital image processing and pattern recognition techniques to assist in diagnosing neurological disorders. In medical practices the posture and movement of a human subject through his/her gait cycle contains information that is used by an experienced clinician to determine the mental health of a patient. An image processing based system can be used to automate this process and produce quanti®ed results. This is achieved by processing, extracting and classifying joint angle information from still images of a human subject's gait. Several new algorithms are devised to process and extract the required information from the images: a new edge extraction technique is used to assist in image segmentation; a technique based on correlating images from dierent parts of a gait is used to obtain complete information about a subject's posture; and an algorithm based on the Hough Transform is used to obtain the limb joint angles and swing distances of a subject. Joint angles and swing distances obtained from normal and patient subjects are then used in training and verifying classi®cations using a feed-forward neural network and a fuzzy clustering algorithm.