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Computer Assisted Diagnosis And Automation In Medical Practice

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Genevieve Warner Learmonth
Genevieve Warner Learmonth

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

Educación
1 de 30
Evolution of Computer assisted diagnosis and automation in Medical Practice Dr Genevieve Warner Learmonth, Honorary Senior Lecturer, Clinical Laboratory Sciences, University of Cape Town
History and development ,[object Object],[object Object],[object Object]
Neural Networks in image recognition ,[object Object],[object Object],[object Object],[object Object],[object Object]
PapNet ,[object Object],[object Object],Tuberculosis epidemic
Support ,[object Object],[object Object]
TB or not TB ? ,[object Object],Then I met Kostas Veropoulos, a mathematical computer scientist who was “ looking for a project”
Mobile TB Diagnosis in South Africa Van / Lab visits peri urban areas. Funded by Pick ‘n Pay
 
The search for bacilli on conventional sputum smears ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Project ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
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)
Test Example: ZN stained slide (sputum smear at 40x magnification after image processing)
Image processing
Test Example: Auramine stained slide (sputum smear at 6 3 0 x magnification after image processing) EDGE DETECTION
Results --- specificity for a single bacillus Auramine stain ZN stain
Conclusions ,[object Object],[object Object],[object Object]
Cost Effectiveness ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Funding ,[object Object],[object Object],[object Object],[object Object],[object Object],Spotlight on africa
 
Presentations at Congress ,[object Object],[object Object],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
Publications and World wide presentations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lack of Interest and Funding in TB epidemics --- 1997/1998 ,[object Object],[object Object],[object Object],[object Object]
Futuristic Visions for Computerised Diagnosis
Finding the bacillus ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
Computing and Image processing ,[object Object],[object Object],[object Object],[object Object]
Image Capture and Global Transmission ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What happened ? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Future has arrived Welcome to the Interscope

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Computer Assisted Diagnosis And Automation In Medical Practice

  • 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
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  • 7. Mobile TB Diagnosis in South Africa Van / Lab visits peri urban areas. Funded by Pick ‘n Pay
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  • 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)
  • 13. Test Example: ZN stained slide (sputum smear at 40x magnification after image processing)
  • 15. Test Example: Auramine stained slide (sputum smear at 6 3 0 x magnification after image processing) EDGE DETECTION
  • 16. Results --- specificity for a single bacillus Auramine stain ZN stain
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  • 24. Futuristic Visions for Computerised Diagnosis
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  • 30. The Future has arrived Welcome to the Interscope