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In the early 1980s, thermography began to be used to detect pain and breast cancer. However, the images were interpreted through the naked eye, and thus subtle differences were difficult to identify. More recently, widespread use of PCs led to the application of computer processing to the analysis of thermal images. For example, Head et al. (1997) reported three methods to calculate temperature differences between the right and left breast to help detect and diagnose breast cancer. Their analysis of 13 patients had better results with their 3rd method than with their methods 1 and 2, but still showed 3 false positives out of 10 patients who were diagnosed as "normal" and 1 false negative out of 3 patients diagnosed with cancer. We applied these authors' three techniques to nine of our patients (6 with a diagnosis of normal and 3 with cancer) and found that only method 3 provided reliable results. With the lower threshold of 1°C suggested by Head et al., we had 2 false positives. However, when we raised the threshold to of normalcy to 1.5°C (instead of 1), we found no false negatives or false positives on this sample of nine patients. Future work should focus on improving the third approach and find new ways of enhancing differences, which would be significant for a correct diagnosis. These preliminary results are encouraging but a properly designed prospective clinical trial needs to be done to show if this technique can play a useful role in the future or not.