Title : Early and automatic breast cancer detection and screening using thermal imaging
Breast cancer is one of the deadliest forms of cancer in women but the disease has a good prognosis when diagnosed early. Existing breast cancer diagnosis devices are mammography, breast ultrasound, breast MRI scan and breast biopsy. But the gold standard for the diagnosis of breast cancer is mammography imaging analysis. The image acquisition system of mammogram is a painful and embarrassing procedure for women involving breast compression. In addition to this, Mammogram use radiation which is risk factor for breast cancer development. Alternative methods have been investigated in the last years, including breast thermography, which does not involve ionizing radiation, pain or contact with the breast. However, the accuracy of these modern techniques still needs to be improved to allow the widespread use in practical applications but automatic detection and screening techniques have brought in an increased accuracy and reduction in false positives and false negatives to the analysis of breast thermograms. This presentation focuses to improve breast cancer detection and screening system by applying the state of art in thermal imaging and artificial intelligence specifically, deep learning methods.