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Architecture for Automatic GLaucoma
Diagnosis and Its Genetic Association Study through Medical Image InformAtics
(AGLAIA)Jimmy Liu Jiang1, Zhang Zhuo1, Wong Wing Kee1, Tan Ngan Meng1, Yin Feng Shou1, Lee Benghai1, Cheng Jun1, Wong Tien Yin2
1: Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore2: Singapore Eye Research Institute
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AGLAIA Single statement
A system for the automated detection of glaucoma from multiple image features of retinal images with possible genetic analysis.
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Glaucoma Has No Cure!
Glaucoma Irreversible loss of optic nerves Leading to blindness 5.7 million glaucoma blind (total 38 million blind in the
world)
BUT: glaucoma can be slowed if detected early Vision loss (functional) Optic nerve damage (imaging)
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Optic Nerve Damage Precedes Vision Loss
No Glaucoma Early Late Stage
Nerve Damaged Severe
Vision Loss
Optic Nerve
Pictures from NIH
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Measure Optic Nerve Damage from Retinal Image - CDR CDR (Cup to Disc Ratio) value is an
important indicator for Glaucoma
Automatic CDR measurement Saving clinician’s time Results reproducible Ideal for mass screening
DiscCup
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Step 1: Disc segmentation
Step 2: Boundary smoothing of the detected disc
Step 3: Cup segmentation
Step 4: Boundary smoothing of the detected cup
Step 5: Intelligent Fusion
AGLAIA
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AGLAIA Framework
Fundus imageFundus image
Genome data
Genome data
Clinical dataClinical data
Intelligentfusion
Glaucoma riskanalysis Report
GWAS
CDR
HemorrhageNotching
PPA KinkRim
Asymmetry
Clinical dataClinical data
MINING
Gradeability Disc Size
Tilted Disc
ISNT RuleVessel Pattern
RNFL
Fundus imageFundus image
Genome data
Genome data
Clinical dataClinical data
Intelligentfusion
Glaucoma riskanalysis Report
GWAS
CDR
HemorrhageNotching
PPA KinkRim
Asymmetry
Clinical dataClinical data
MINING
Gradeability Disc Size
Tilted Disc
ISNT RuleVessel Pattern
RNFL
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13 Image cues used in AGLAIAAGLAIA aims to provide a multi-modality system that captures globally a range of
parameter that is indicative of early glaucoma damage. AGLAIA will automatically measure and assess the following features objectively and quantitatively, features which are currently evaluated subjectively by glaucoma specialist in clinical practice: Cup-to-disc ratio (CDR) – further refinement will be made based on initial algorithms
developed in ARGALI Disc hemorrhage (DH) Thinning of the NRR (NeuroRetinal Rim) Notching of the NRR Compliance of NRR width by ‘ISNT Rule’ (inferior≥superior≥nasal≥temporal) Inter-eye asymmetry Parapapillary atrophy (PPA) Blood vessel pattern analysis Blood vessel kink analysis Tilted Disc - quantify the degree of tilting based on the disc contour Disc Size - automatically classify disc size to "large, medium or small" categories based on
automatic disc measurement Gradeability – analyze the image and determine gradeability Check the presence of RNFL (Retinal Nerve Fiber Layer) defect.
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Image Datasets
Datasets used for testing Retinal Vessel and Glaucoma Subtype Study
(RVGSS) 65 glaucoma images
Singapore Indian Chinese Cohort (SICC) 224 non-glaucoma images
Clinical CDR provided
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Test Result Summary
Specificity 0.88
Sensitivity 0.95
Average absolute CDR error (wrt clinical CDR) 0.14
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AGLAIA Market Potential
The Technology can be readily implemented in currently available instruments for ocular screening without extensive modifications.
The Technology could potentially be of interest to ocular instrument makers to incorporate the Technology into their equipment, and to health institutions such as clinics and hospitals for glaucoma screening.
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AGLALI CDR Absolute Error Distribution
Error Interval
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Receiver Operating Characteristic (ROC) Curve
AUC Sensitivity Specificity ICC Maximum Std. Deviation
0.94 0.954 0.88 0.553 0.65 0.12