Medical diagnostic support system based on breast thermography using Raspberry Pi and cloud computing

Breast thermography is a promising medical imaging technique for the detection of breast cancer. However, providing robust and portable computer-aided diagnostic system remains tedious task. In this paper, based on developed implemented Raspberry Pi 4 using cloud computing services to provide power needed machine learning algorithms. Image processing techniques such as pre-processing segmentation are employed achieve an adequate feature extraction The Support Vector Machine classifier used in final stage classify normal or abnormal. According experimental results, proposed has shown high performance both classification steps. Furthermore, low computation time was obtained when capabilities with Pi. We conclude that implementation decision support especially services, can be reliable tool radiologists predict abnormalities even rural backcountry where there lack health services.