AI based
Diabetic Retinopathy Screening System
DRISTI analyses retinal
fundus images for Diabetic Retinopathy lesions
and directs suspicious cases for detailed
ophthalmologist's review. Most of the negative
cases can be screened out without
ophthalmologist's intervention
Brief
Description
Diabetic Retinopathy (DR) is
the damage caused to retina by complications of
diabetes which can eventually lead to blindness.
Presently the ratio of ophthalmologist to
general population is 1 : 80,000 which makes it
nearly impossible to implement screening
programs manually with human expertise alone.
DRISTI, using quantitative image analysis
algorithms, analyses retinal fundus images for
DR lesions and directs DR suspicious cases for
detailed ophthalmologist review. DR negative
cases are screened out without ophthalmologist
intervention.
Features and Technical Specifications
-
Analyses images and
automatically classifies retina as either
Non-DR or suspicious of DR.
-
Patient prioritization based
on automated severity scoring.
-
Only cases having suspicion
of DR need ophthalmologist's review.
-
Increase screening
efficiency and reduce workload of
ophthalmologists by up to 78%.
-
Automated assessment of
retinal image quality and real-time operator
notification for re-imaging.
-
Detects retinal pathologies
like micro-aneurisms, dot, blot, flame
haemorrhages, exudates, cotton-wool-spots
automatically.
-
Detects optic disc and
retinal blood vessels automatically.
-
Intuitive GUI for automated
analysis of image, patient or patient batch.
-
Systematic storage of
patient details and automated analysis
results.
-
Reports automated analysis
results.
-
Application in population
screening for DR.
-
Can be operated even by a
non-ophthalmologist
Platform required(if any)
-
Fundus camera
-
40-50 deg field of view
-
Min 3MP color sensor
-
Software for image capture
and archival along with patient details
-
Provision to capture image
in lossless formats like BMP, TIFF etc.
Workstation
-
Core i5, 3 Ghz with 4GB RAM
or better configuration
-
Monitor with 1920x1080
resolution
-
Windows 7 64 bit OS
Workspace
-
Motorized table with height
adjustment for mounting the fundus camera
-
Enclosed room with
controlled lighting, so as not to interfere
with the imaging
Download Brochure
Contact Details for Techno Commercial
Information
DR ALEXANDER G
Group Head,
Health Informatics & Software Technology Group,
C-DAC,Thiruvananthapuram
email - alex@cdac.in |