1. MCS3020- Research Project
Macular Thickness Diagnosis in 3D
Environment
UNIVERSITY OF COLOMBO SCHOOL OF COMPUTING

2. SUPERVISED BY:
 Dr. Prasad Wimalaratne
 S.W.K.P. Abeysinghe 2009MCS002
STUDENT:

3. Sections
 Introduce research domain
 Aims & Objectives
 Literature Review
 Design & Methodology
 Limitations
 Future work

4. OCT (Optical coherence
tomography)
 Captures micrometer-resolution,
three-dimensional images from
within optical scattering media
(biological tissue)
 Usages
◦ In ophthalmology – Obtained detail
images within the retina.
◦ In cardiology – Help diagnose coronary
artery disease.

5. World Health Organization
(WHO) (Fact sheet,2013)
 There are 285 million people are
estimated to be visually impaired in
worldwide and about 90% of them live
in developing countries.
 80% of all visual impairment can be
avoided or cured if it identifies as early
as possible.
 This is possible through OCT reports
in ophthalmology.

6. Problem
 Not all medical centers / hospitals
having OCT scanning facility.
 Doctor needs to identifies the disease
using the printed report.
 Manually needs to keep patient report
history.
 Comparison can be done by checking
each reports manually.

7. Aim
 Create a platform independent 3D eye
diagnosing tool.
◦ Show the report as a 3D model and let
doctors easily diagnose.
◦ Let doctors to compare multiple scans at
once within a single view.
◦ Keep patient’s OCT report history.

8. Objectives
 Identify each color thickness in each
OCT machine from the false-color
representation in the report.
 Model 3D image on the report using
the OCT machine color thickness
map.
 Produce a simple, light weight DBMS
to handle and keep scanned data of
the patient.

9. Literature Review
 On various OCT scan based 3D eye diagnosing
products.
 On how to examine each OCT machine thickness
based color map.
 On various data structures to handle functionality of the
color map.
 On color comparison techniques to identify thickness
from the color map.
 On various 3D modeling tools.
 On various DBMS to store data and image/pdf storing
techniques.
 On various techniques to improve the product external
and internal qualities like correctness, performance,
robustness, reusability and maintainability etc.

10. Sample OCT report
 Inputs
◦ ILM-RPE view
◦ Color map

11. Design & Methodology
 Thickness Map Generation by Color

12. Design & Methodology
Cont…
 Thickness color map generator

13. Design & Methodology
Cont…
 Report thickness identification using
color map
◦ Need to compare the most suitable color
with the color map
◦ Use the formula of ;
 Low-cost approximation with gamma
correction

14. Design & Methodology
Cont…
 OCT report thickness identification

15. Design & Methodology
Cont…
 System architecture

16. Business layer class diagram

17. Storage structure

18. Limitations
 Limited number of OCT report
samples available due to the personal
information of the patient.
 Color scales/ color maps will differ by
the OCT machine.
 If OCT report was not in a good quality
then there might have some thickness
identification issues.

19. Future Work
 Can be use more advanced image processing
technologies to increase performance of the 3D
modelling tool.
 Increase security options and advanced features like
the report comparison to be handled in parallel with
multiple users.
 Develop this product to use in mobile devices.
 With the time of the usage has been increased of the
system, a data mining module can be developed.
 Report generation and email can also be provided to
the user.
 All the business components are made generic way,
hence this system also supports to developed to handle
other OCT based examinations.
 Finally, user interface can also be improved.