Research and applications: Automatic glaucoma diagnosis through medical imaging informatics
نویسندگان
چکیده
BACKGROUND Computer-aided diagnosis for screening utilizes computer-based analytical methodologies to process patient information. Glaucoma is the leading irreversible cause of blindness. Due to the lack of an effective and standard screening practice, more than 50% of the cases are undiagnosed, which prevents the early treatment of the disease. OBJECTIVE To design an automatic glaucoma diagnosis architecture automatic glaucoma diagnosis through medical imaging informatics (AGLAIA-MII) that combines patient personal data, medical retinal fundus image, and patient's genome information for screening. MATERIALS AND METHODS 2258 cases from a population study were used to evaluate the screening software. These cases were attributed with patient personal data, retinal images and quality controlled genome data. Utilizing the multiple kernel learning-based classifier, AGLAIA-MII, combined patient personal data, major image features, and important genome single nucleotide polymorphism (SNP) features. RESULTS AND DISCUSSION Receiver operating characteristic curves were plotted to compare AGLAIA-MII's performance with classifiers using patient personal data, images, and genome SNP separately. AGLAIA-MII was able to achieve an area under curve value of 0.866, better than 0.551, 0.722 and 0.810 by the individual personal data, image and genome information components, respectively. AGLAIA-MII also demonstrated a substantial improvement over the current glaucoma screening approach based on intraocular pressure. CONCLUSIONS AGLAIA-MII demonstrates for the first time the capability of integrating patients' personal data, medical retinal image and genome information for automatic glaucoma diagnosis and screening in a large dataset from a population study. It paves the way for a holistic approach for automatic objective glaucoma diagnosis and screening.
منابع مشابه
Automatic glaucoma diagnosis through medical imaging informatics
Department of Ocular Imaging, Institute for Infocomm Research, Singapore, Singapore Department of Neural & Biomedical Technology, Institute for Infocomm Research, Singapore, Singapore Department of Computer Engineering, Nanyang Technological University, Singapore, Singapore Singapore Eye Research Institute, Singapore, Singapore Singapore National Eye Centre, Singapore, Singapore National Univer...
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ورودعنوان ژورنال:
- Journal of the American Medical Informatics Association : JAMIA
دوره 20 6 شماره
صفحات -
تاریخ انتشار 2013