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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
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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.
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12. Extraction of tumour portions-Output Gray scale extracted portion Red plane –Extracted portion of an Carcinoma image
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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%
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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.