Computer Assisted Diagnosis And Automation In Medical Practice

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This higlights an initiative to develop a computerised method of recognising TB bacilli on conventional sputum smears using digital image recognition. This method would speed up the screening process, and enable medical staff to carry on witth the enormous diagnostic burden facing them in South Africa. References K Veropoulos and Gm warner learmonth

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Computer Assisted Diagnosis And Automation In Medical Practice

  1. 1. Evolution of Computer assisted diagnosis and automation in Medical Practice Dr Genevieve Warner Learmonth, Honorary Senior Lecturer, Clinical Laboratory Sciences, University of Cape Town
  2. 2. History and development <ul><li>Coulter Counter machine introduced in 1968 to count erythrocytes (red blood cells) </li></ul><ul><li>In 1980’s attempts were made in UK to develop a machine to detect abnormal cells ( and organisms) on pap smears. Led by Dr Nassiem Husain. </li></ul><ul><li>Computer technology not advanced enough at that time. </li></ul>
  3. 3. Neural Networks in image recognition <ul><li>In 1990’s neural networks were regarded as being the solution to the problem of image recognition. </li></ul><ul><li>Mark Rutenberg at NASA was working at surveillance of the night skies to intercept SCUD missiles in Gulf War </li></ul><ul><li>Dr Laurie Mango, a cytologist, involved in possible automation in diagnosis sat beside him at a dinner party. </li></ul><ul><li>They discovered that they were doing the same thing at different magnitude ! </li></ul><ul><li>PapNet was conceived and born. </li></ul>
  4. 4. PapNet <ul><li>When I was asked to present Clinical trial results for PapNet in 1996, I learned about the use of neural networks in image recognition, at Bristol University Dept of Engineering and Mathematics. </li></ul><ul><li>My interest was in image recognition of cells and bacteria/ fungi </li></ul>Tuberculosis epidemic
  5. 5. Support <ul><li>I phoned PapNet in the USA, asked them if they could use the PapNet machine to find TB bacilli on ZN stained sputum. They agreed, but they were disinclined to “waste time on it” as all their funding was dedicated to cervical Pap smear screening. </li></ul><ul><li>My son proposed that that one day it would be possible to recognise malaria, leprosy, meningococcus, organisms in drinking water, fungi etc. using similar computer imaging methods ! </li></ul>
  6. 6. TB or not TB ? <ul><li>Suddenly I realised that as TB bacilli as they were unique in shape, size and staining properties, (literally a case of “TB or not TB”), neural networks could be applied to the search for TB bacilli </li></ul>Then I met Kostas Veropoulos, a mathematical computer scientist who was “ looking for a project”
  7. 7. Mobile TB Diagnosis in South Africa Van / Lab visits peri urban areas. Funded by Pick ‘n Pay
  8. 9. The search for bacilli on conventional sputum smears <ul><li>Boring </li></ul><ul><li>Labour intensive </li></ul><ul><li>Requires experienced </li></ul><ul><li>senior laboratory scientists </li></ul><ul><li>High False Negative Rate </li></ul><ul><li>Low morale </li></ul><ul><li>Recruitment of screening staff difficult </li></ul><ul><li>Remuneration of staff </li></ul>
  9. 10. The Project <ul><li>The slides, were examined by GML at the digital microscope with KV using digital imaging facility at Bristol University in 1997. </li></ul><ul><li>5,000 individual bacilli were identified and images captured. </li></ul><ul><li>Image processing performed. </li></ul><ul><li>Learning </li></ul><ul><li>Then system was challenged with 100 more images of typical TB bacilli. </li></ul><ul><li>No funding available ---- no interest in TB. </li></ul>
  10. 12. Morphology of and types of TB bacilli Mycobacterium Tuberculosis (2–4μm x 0.3–0.5μm) Mycobacterium bovis (1.5–1.9μm) Mycobacterium avium (1.0–1.8μm x 0.5μm) Mycobact. kansasii ( usually 4–5μm x 0.3μm)
  11. 13. Test Example: ZN stained slide (sputum smear at 40x magnification after image processing)
  12. 14. Image processing
  13. 15. Test Example: Auramine stained slide (sputum smear at 6 3 0 x magnification after image processing) EDGE DETECTION
  14. 16. Results --- specificity for a single bacillus Auramine stain ZN stain
  15. 17. Conclusions <ul><li>Computer assisted diagnosis TB feasible with very encouraging results </li></ul><ul><li>Radical improvement in accuracy </li></ul><ul><ul><li>recognition of single bacillus > 80%, thus recognition of multiple bacilli in a smear yields a very high diagnostic accuracy </li></ul></ul>
  16. 18. Cost Effectiveness <ul><li>Cost effective for population screening </li></ul><ul><ul><li>Cape Town: over 8,000 slides/month screened at $2/slide </li></ul></ul><ul><ul><li>assuming 2 systems processing 200 slides/day each, click charge $25, estimated cost of machine at $20K, then annual saving is 75% for client ( estimation based on year 2000 prices ) </li></ul></ul><ul><ul><li>with computer components becoming cheaper monthly, the above figures could change dramatically </li></ul></ul><ul><li>Socio-economically effective </li></ul><ul><ul><li>disease more efficiently contained in adult population </li></ul></ul><ul><li>1 billion TB tests annually </li></ul>
  17. 19. Funding <ul><li>TB is a disease of poverty </li></ul><ul><li>Highly contagious airborne disease </li></ul><ul><li>Attacks immunosuppressed persons </li></ul><ul><li>Infancy, puberty, pregnancy, illness, old age </li></ul><ul><li>HIV infected persons are particularly susceptible --- The Terrible Twins </li></ul>Spotlight on africa
  18. 21. Presentations at Congress <ul><li>Presented in Chicago at Analytical and Quantitative Cytology 1997 </li></ul><ul><li>Presented in Hong Kong Cytopathology Congress 1998 </li></ul>Automated Identification of Tubercle Bacilli in Sputum. Veropoulos K, Learmonth G, Campbell C, Knight B, Simpson J, Journal of Analytical & Quantitative Cytology and Histology 1999 Vol.21, 4, 277 – 281
  19. 22. Publications and World wide presentations <ul><li>The Automated identification of Tubercle bacilli using Image Processing and Neural Computing techniques. </li></ul><ul><li>K Veropoulos, C Campbell, G. Learmonth, B. Knight, J. Simpson, </li></ul><ul><li>Perspectives in Neural Computing: Proceedings of the 8th International Conference on Artificial Neural Networks, Skovde Sweden. 2-4 September 1998 . Volume 2 pp 797 - 802. </li></ul><ul><li>Springer ISBN 3 540 76263 9 </li></ul><ul><li>Image processing and neural computing used in the diagnosis of tuberculosis </li></ul><ul><li>Veropoulos, K. Campbell, C. Learmonth, G. Fac. of Eng., Bristol Univ.; 20 Oct 1998 </li></ul><ul><li>Intelligent Methods in Healthcare and Medical Applications (Digest No. 1998/514), IEE Colloquium on page(s): 8/1-8/4York, UK References Cited: 10 INSPEC Accession Number: 6128756 </li></ul>
  20. 23. Lack of Interest and Funding in TB epidemics --- 1997/1998 <ul><li>“ TB is not a problem in the UK or USA” </li></ul><ul><li>Pharmaceutical Companies viewed any attempt to curtail the disease by rapid diagnosis/ identification of TB infected persons as a threat to their business of R&D of new anti TB drugs. </li></ul><ul><li>Very few foresaw the danger of TB spreading hand in hand with the Immunosuppressed victims of HIV/AIDS </li></ul><ul><li>THE TERRIBLE TWINS </li></ul>
  21. 24. Futuristic Visions for Computerised Diagnosis
  22. 25. Finding the bacillus <ul><li>Microscope: </li></ul><ul><li>Simple </li></ul><ul><li>Purpose Built </li></ul><ul><li>Inexpensive </li></ul><ul><li>Portable </li></ul><ul><li>User Friendly </li></ul><ul><li>Microscopes have not changed much since van Leeuwenhoek persuaded Vermeer to use one in 1642 ! </li></ul><ul><li>The most commonly used microscope in labs today are expensive, complicated and have too many gadgets. </li></ul><ul><li>For screening sputum for bacilli a very simple microscope is required. </li></ul>
  23. 27. Computing and Image processing <ul><li>User Friendly </li></ul><ul><li>PC /Laptop </li></ul><ul><li>Simputer </li></ul><ul><li>Hand Held Computer eg Blackberry </li></ul>
  24. 28. Image Capture and Global Transmission <ul><li>“ Smart” camera </li></ul><ul><li>Coolscope </li></ul><ul><li>Built in Digital Camera </li></ul><ul><li>TRANSMISSION of IMAGES 1998 </li></ul><ul><li>from home computer in Bristol </li></ul><ul><li>Project “ Cybercytology” with </li></ul><ul><li>colleagues in Bangladesh </li></ul><ul><li>Global transmission of Images </li></ul><ul><li>Cyber Diagnosis </li></ul><ul><li>2 nd Opinion </li></ul>
  25. 29. What happened ? <ul><li>No further work was done on this TB project. </li></ul><ul><li>KV awarded a PhD at Bristol University 1999 </li></ul><ul><li>KV went to the USA … University of Reno </li></ul><ul><li>Best Entrepreneur of the Year award at Bristol University in 2001 to GML and KV </li></ul><ul><li>In February 2006, a phone call from NASA </li></ul><ul><li>Our work, found in their archives; “would I assist them in driving this initiative forward” </li></ul><ul><li>The company Interscopic was born. The Interscope was conceived over Internet calls and fertilised in Cyberspace ! </li></ul>
  26. 30. The Future has arrived Welcome to the Interscope

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