1. Norbert GAL and Vasile STOICU-TIVADAR E-mail: norbert.gal@aut.upt.ro “ Politehnica” University of Timisoara, Department of Automation and Applied Informatics, Faculty of Automation and Computers, EFMI Special Topic Conference STC2011 “ E-salus trans confinia sine finibus – e-Health Across Borders Without Boundaries”

2. Universal representation for Fuzzy Inference System for medical image interpretation Algorithm to create the representation

3. Information is divided on two levels Semantic level Cognitive association Linguistic variable (ex: 10 week fetus) Numerical level Numerical algorithms Matrix or other numerical variable

4. Interpretation Simulation (MatLab) Interpretation Implementation (programming language) *.fis file XML source code XML

5. Numerical data Data fuzzyfication Linguistic data processing & result verification Diagnosis display Segmentation & feature extraction

6. “ input 1 :active MF nr ”“input 2 : active MF nr ” …. “input 5 : active MF nr ”, “output 1 : active MF nr ” “output 2 : active MF nr ” (“rule weight”) : “operator (1  AND; 2  OR )” [System] Name='Image-Interpretation' Type='mamdani' Version=2.0 NumInputs=5 NumOutputs=2 NumRules=3 AndMethod='min' OrMethod='max' ImpMethod='min' AggMethod='max' DefuzzMethod='centroid' [Input1] or [Output1] Name='Shape' Range=[0 1] NumMFs=5 MF1='sh_1':'trapmf',[0 0.1 0.2 0.3] MF2='sh_2':'trapmf',[0.2 0.3 0.4 0.5] MF3='sh_3':'trapmf',[0.4 0.5 0.6 0.7] MF4='sh_4':'trapmf',[0.6 0.7 0.8 0.9] MF5='sh_5':'trapmf',[0.8 0.9 1 1.1] [Rules] 1 2 1 2 2, 2 0 (1) : 1 2 1 5 3 1, 0 2 (1) : 1 4 3 2 2 2, 1 0 (1) : 1

7. Rule 3: If (Shape is sh_4) and (Size is large) and (Histogram is dark gray) and (X-axel is center) and (Y-axel is Middle) then (Organ is liver) Rule 1: If (Shape is sh_1) and (Size is medium) and (Histogram is black) and (X-axel is center) and (Y-axel is Middle) then (Organ is gallbladder) Rule 2: If (Shape is sh_2) and (Size is small) and (Histogram is white) and (X-axel is right) and (Y-axel is low) then (Abnormality is Gallstone)

8. Interpretation Simulation (MatLab) *.fis file (text) <?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot;?> <fuzzyInference> <System> <Name>Image-Interpretation</Name> <Type>mamdani</Type> <Version>2.0</Version> <NrInput>5</NrInput XML Universal format Parsing

9. The XML file has the same logical structure as the “*.fis” file Step 1 Step 2 Step 3 input/output variables membership functions name, input/output nr nr of rules other properties Parsing of the rules

10. *.fis (text file) Identify the primary data: name, type, input nr, output nr, rule nr, and-, or-, imp-, agg-, defuzzmethod. Create the System description in the XML Input nr<>0 Identify input data: Name, range, nr of MFs Create the input part in the XML Mf nr<>0 No Identify membership function (exp: MF1='in1':'trapmf',[-0.36 -0.04 0.2 0.3]) Yes Create the MF in XML Output

11. Output Output nr<>0 Identify output data: Name, range, nr of MFs Create the output part in the XML Mf nr<>0 No Identify membership function (exp: MF1='in1':'trapmf',[-0.36 -0.04 0.2 0.3]) Yes Create the MF in XML Rules nr<>0 Yes No Identify rule components and operators (AND or OR) Create rules in the XML file Complete XML file

12. <?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot;?> <fuzzyInference> <System> <Name>Image-Interpretation</Name> <Type>mamdani</Type> <Version>2.0</Version> <NrInput>5</NrInput> <NrOutput>2</NrOutput> <NrRules>3</NrRules> <AndMethod>min</AndMethod> <OrMethod>max</OrMethod> </System> <Input> <Name>Shape</Name> <Range A=&quot;0&quot;B=&quot;1&quot;/> <MF Nr=&quot;5&quot;/> <Labels> <Sh_1 a=&quot;0&quot;b=&quot;0,1&quot;c=&quot;0,2&quot;d=&quot;0,3&quot;/> <Sh_2 a=&quot;0,2&quot;b=&quot;0,3&quot;c=&quot;0,4&quot;d=&quot;0,5&quot;/> ………………………………………… . </Labels> </Input> Input/Ouput variables System (fis properties)

13. MatLab FIS editor *.fis file Converter prototype <?xml version=&quot;1.0&quot;?> <FuzzyInference> <System>Name='Image-Interpretation' Type='mamdani' Version=2.0 NumInputs=5 NumOutputs=2 NumRules=3 AndMethod='min' <Rules>1 2 1 2 2, 2 0 (1) : 1 2 1 5 3 1, 0 2 (1) : 1 4 3 2 2 2, 1 0 (1) : 1 </Rules> </FuzzyInference> Fis XML Future work: image interpretation

14. XML  simple & extensive representation User  complex expressions & rules XML update fuzzy algorithms & inference engine easy functionality extension no source code manipulation interpretation system XML modeling environment