This document describes a deep learning solution to better diagnose oral diseases from dental radiographs (OPGs). A team of students conducted a survey of dental students and found that OPGs can be difficult to diagnose and misdiagnoses sometimes occur. The proposed solution uses convolutional neural networks to build classifiers to detect oral diseases like caries, cysts and tumors from OPGs. It will also apply image processing for tasks like teeth numbering and gender detection. The team has collected 2200 anonymized OPGs and will label them with dentist help. They plan to develop a web app backend with a client interface that allows uploading OPGs for automated diagnosis to assist dentists. Demo functionality was shown for tasks like caries detection and individual tooth labeling

1. A Deep Learning solution to better diagnose oral
diseases
IBA FCS Final Year Projects

2. Team
Members
Omer Farooq Ahmed Maaz Hasan Hassan Saeed

3. Project
Supervisor
Dr. Imran N. Junejo - Associate
Professor
• PhD (Computer Science), School
of Electrical Engineering and
Computer Sciences, University of
Central Florida, Orlando, FL, - 2007
• MS (Computer Science), School
of Electrical Engineering and
Computer Sciences, University of
Central Florida, Orlando, FL, - 2005
• BSCS , Department of Computer
Science, University of Arizona, Tucson,
AZ, U.S.A - 2001

4. Dental
Radiographs
● Radiographs in dentistry can help dental practitioners
diagnose numerous oral and maxillofacial diseases.
● Radiographs are often difficult to read and present a
number of challenges to dentists and diagnosticians
when determining abnormalities.
● Most commonly used radiography technique is OPG; a
panoramic or wide view x-ray of the lower face, which
displays all the teeth of the upper and lower jaw on a
single film.

5. A SAMPLE OPG

6. Viability
Survey
● We conducted a survey with undergraduate
dental college students at the Dr. Ishrat ul
Ebad Institute of Oral Sciences at DUHS
● The questions and their results are shown in
the following slides

7. Misdiagnosis

8. Trouble
diagnosing
an OPG

9. Teeth
Numbering

10. Need of an
Assistive
System

11. Viability of a
diagnostic
application

12. Our Solution
● Teach computers to diagnose an OPG to assist a
doctor’s diagnosis.
● Our project aims to use Deep Learning
techniques with Convolutional Neural Networks to
build classifiers that can accurately detect certain
oral and maxillofacial diseases.
● The diseases include caries, cysts and tumors as
well as diagnosing incorrect root canal
treatments.
● We will also apply various other image processing
steps to annotate the test OPG with teeth
numbering, gender detection etc.

13. THE DATA
Information about the data used

14. Data Collection
● Dataset for this project are panoramic dental x-rays (OPGs).
● We are still in the phase of data gathering.
● We have currently collected 2200 anonymised OPGs from Ojha hospital.
● We have reached an agreement with the Liaquat Dental College at Darul Seh
Hospital to collect all OPGs that they conduct in the next two months.

15. ● We will solicit the services of 6 senior dentists from different institutions (to
achieve low bias) to label the data for us
● We will build a web based application that connects to a database server that
hosts all of our segmented datasets (teeth).
Data Labelling

16. Data
Processing
Methodology

17. The
Technologies
Used
Front End Client
Back End Database

18. The
Technologies
Used
Programming
Language
Machine Learning
Libraries

19. Final
Products
● Hosts the trained CNN
classifiers for both disease detection and
teeth segmentation.
● Runs in the background of the OPG
technician’s computer
● Uploads every new OPG to the server
application for diagnosis
● Used by Dentists to view past week’s OPG
diagnoses
● Dentist can upload an OPG x-ray and get
diagnosis within seconds

20. The Demo
Instance Segmentation
in action

21. The Demo

22. The Demo
Caries Detection
labelled image

23. The Demo
Individual labelled tooth
(caries
positive/negative)

24. The Demo
Upload a dental OPG
for diagnosis

25. The Demo
Diagnosed Image

26. THANK YOU!
A deep learning solution to better
diagnose oral diseases