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Artificial intelligence in medical image processing


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Artificial intelligence is improving approaches to image processing in medical images.

Published in: Health & Medicine

Artificial intelligence in medical image processing

  1. 1. Artificial intelligence in medical image processing would be effective enough to help radiologists? Dr. F. Jahedi January 2014 IRAN - SHIRAZ
  2. 2. WATSON Jeopardy
  3. 3. Giant Knowledge Base AI Algorithms Natural Language Processing
  4. 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. 5. Images Patient Data Medical Knowledge Decision Support Image Processing Decision Procedure Image Display Patient Summary KB Browser Decision Summary
  6. 6. Medicine Radiology Artificial Intelligence Recorded Data Digitized Data Image Processing Segmentation / etc. Medicine Radiology ANN Genetic Fuzzy Hybrid
  7. 7. Artificial Intelligence Programs which enable computers to achieve human-level performance in cognitive tasks
  8. 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. 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
  10. 10. MedicalDiagnosis SupportSystem
  11. 11. 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
  12. 12. 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’
  13. 13. 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
  14. 14. 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
  15. 15. You can tell whether a person is Clever by his/her Answers You can tell whether the person is Wise by his/her Questions
  16. 16. Thank You