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A novel automated hot spot detection system for tracking metastasis in Digital Infrared Thermal Images Madhumitha Raghu  Divya.N  N.Sriraam  B.Venkatraman   P.Manoj Niranjan
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object]
Overview of Breast Cancer ,[object Object],[object Object]
 
Current status of breast cancer detection ,[object Object],[object Object],[object Object]
Validation Carcinoma (Ca) Breast – Right  Upper medial quadrant mass.  Suggestive of Ca by USG and mammography and confirmed by Fine Needle Aspiration Cytology.  Mass detected by mammography
Validation FNAC - Results Highly cellular smear with Pleumorphism increased nucleo cytoplasmic ratio and prominent  nuclei which is suggestive of carcinoma.
 
Gray Scale Processing-Inference ,[object Object],[object Object]
RGB Processing -Inference ,[object Object]
Temperature mapping ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Extraction of tumour portions-Output Gray scale extracted portion Red plane –Extracted portion of an Carcinoma image
SVM Classification ,[object Object],[object Object]
Observation S.NO. FEATURES CLASSIFICATION PERCENTAGE 1. Entropy Difference between left and right sides of Red and Green Planes 77% 2. Entropy Difference between left and right sides of Red and Blue Planes 88.889% 3. Entropy Difference between left and right sides of Green and Blue Planes 83.33% 4. Red Plane – Maximum kurtosis of left and right sides 77.778% 5. Green Plane – Maximum kurtosis of left and right sides 77.778% 6. Red Plane – Maximum Eigen values of left and right sides 66.67% 7. Blue Plane – Maximum Eigen values of left and right sides 72.2%
Feed Forward Classifier ,[object Object],[object Object]
Progress of the work Analysis Inference 1. Gray scale processing Elimination – As no significant trend observed 2. RGB color processing Work to be extended for all the 16 colors 3. 16 color segmentation following color temperature mapping As it involves temperature which co-relates  with the body temperature, the feature matrix can be used as inputs to the classifier.
Conclusion ,[object Object],[object Object]
Conclusion ,[object Object],[object Object],[object Object]
Future Direction ,[object Object]
References ,[object Object],[object Object],[object Object],[object Object],[object Object]

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A novel automated hot spot detection system for tracking metastasis in digital infrared thermal images (1)

  • 1. A novel automated hot spot detection system for tracking metastasis in Digital Infrared Thermal Images Madhumitha Raghu Divya.N N.Sriraam B.Venkatraman P.Manoj Niranjan
  • 2.
  • 3.
  • 5.
  • 6. Validation Carcinoma (Ca) Breast – Right Upper medial quadrant mass. Suggestive of Ca by USG and mammography and confirmed by Fine Needle Aspiration Cytology. Mass detected by mammography
  • 7. Validation FNAC - Results Highly cellular smear with Pleumorphism increased nucleo cytoplasmic ratio and prominent nuclei which is suggestive of carcinoma.
  • 9.
  • 10.
  • 11.
  • 12. Extraction of tumour portions-Output Gray scale extracted portion Red plane –Extracted portion of an Carcinoma image
  • 13.
  • 14. Observation S.NO. FEATURES CLASSIFICATION PERCENTAGE 1. Entropy Difference between left and right sides of Red and Green Planes 77% 2. Entropy Difference between left and right sides of Red and Blue Planes 88.889% 3. Entropy Difference between left and right sides of Green and Blue Planes 83.33% 4. Red Plane – Maximum kurtosis of left and right sides 77.778% 5. Green Plane – Maximum kurtosis of left and right sides 77.778% 6. Red Plane – Maximum Eigen values of left and right sides 66.67% 7. Blue Plane – Maximum Eigen values of left and right sides 72.2%
  • 15.
  • 16. Progress of the work Analysis Inference 1. Gray scale processing Elimination – As no significant trend observed 2. RGB color processing Work to be extended for all the 16 colors 3. 16 color segmentation following color temperature mapping As it involves temperature which co-relates with the body temperature, the feature matrix can be used as inputs to the classifier.
  • 17.
  • 18.
  • 19.
  • 20.