Artificial intelligence in medical image processing shows promise to help radiologists in three key ways: 1) AI algorithms can analyze millions of current medical journals and cross-reference symptoms from cancer patients to make hypotheses and assist in decision making. 2) Image processing and segmentation techniques using artificial neural networks, fuzzy logic, and other methods can help analyze medical images like MRI, CT, ultrasound and more to identify patterns and help diagnose conditions. 3) Hybrid intelligent systems combine approaches like neural networks and genetic algorithms to automatically train systems and generate architectures to further improve analysis of medical images and decision support.

1. Artificial intelligence
in medical image processing
would be effective enough
to help radiologists?
Dr. F. Jahedi
January 2014
IRAN - SHIRAZ

2. WATSON Jeopardy

3. Giant
Knowledge Base
AI
Algorithms
Natural Language Processing

4. In
15 sec.
Millions of current medical
journals to make hypothesis
Millions of cross reference of symptoms
of cancer patients
Analyze 200 Million pages of clinical
data

5. Images
Patient
Data
Medical
Knowledge
Decision
Support
Image
Processing
Decision
Procedure
Image
Display
Patient
Summary
KB
Browser
Decision
Summary

6. Medicine
Radiology
Artificial Intelligence
Recorded
Data
Digitized
Data
Image Processing
Segmentation / etc.
Medicine
Radiology
ANN Genetic Fuzzy Hybrid

7. Artificial Intelligence
Programs
which enable computers
to achieve
human-level performance
in cognitive tasks

8. They are designed to
Assist in tasks
that rely on the manipulation of
data and knowledge.
Artificial Neural Networks (ANNs)
Fuzzy Expert Systems
Evolutionary Computation
Hybrid Intelligent Systems
Systems

9. ANN
Ability to classify and recognize patterns
ANNs have been used to interpret:
• plain radiographs
• ultrasound
• CT
• MRI
• Radioisotope scans
In radiology both are possible as inputs:
• human observations
• direct digitized images

11. MedicalDiagnosis
SupportSystem

12. Fuzzy
expert
systems
The science of
reasoning, thinking and inference
that recognizes and uses
the real world phenomenon
that everything is a matter of degree
They have been applied to characterize
• ultrasound images of the breast
• ultrasound and CT scan images of liver lesions
• MRI images of brain tumors

13. Evolutionary
computation
They have been used in:
• Computerized analysis of mammographic
micro-calcification,
• MRI segmentation of brain tumors to measure
the efficacy of treatment strategies
• Analyzing computerized 2-D images to
diagnose malignant melanomas
imitates the mechanism of
natural selection and
survival of the fittest
in solving real-world problems
Most widely used form for medical applications are ‘Genetic Algorithms’

14. Hybrid
intelligent
systems
The popular ones are:
•ANNs for designing fuzzy systems
•Fuzzy systems for designing ANNs
•Genetic Algorithms for
automatically training and
generating neural network
architectures
Analysis of microcalcification on
digital mammograms

15. However, in spite of earlier optimism, medical AI
technology has not been embraced with enthusiasm.
One reason for this is the attitude of the clinicians
towards technology being used in the decision-making
process.
Paradoxically, there is no doubt in accepting the
• Biochemical results generated from an auto-analyser
• Images produced by MRI

16. You can tell whether a person is
Clever
by his/her
Answers
You can tell whether the person is
Wise
by his/her
Questions

17. Thank You