Breast cancer is the most common malignant tumor in females around the world, representing 25.2% of all cancers in women. About 1.7 million women were diagnosed with breast cancer worldwide in 2012 with a death rate of about 522,0001,2. The most frequently used methods in breast cancer screening are imaging methods, i.e. ultrasonography and mammography. A common feature of these methods is that they inherently involve the use of expensive and advanced equipment. The development of advanced computer systems allowed for the continuation of research started already in the 1980s3 and the use of contact thermography in breast cancer screening. The physiological basis for the application of thermography in medical imaging diagnostics is the so-called dermothermal effect related to higher metabolism rate around focal neoplastic lesion. This phenomenon can occur on breast surface as localized temperature anomalies4. The device developed by Braster is composed of a detector that works on the basis of thermotropic liquid crystals, image acquisition device and a computer system for image data processing and analysis. Production of the liquid crystal detector was based on a proprietary CLCF technology (Continuous Liquid Crystal Film). In 2014 Braster started feasibility study to prove that there is a potential for artificial intelligence in early breast cancer detection using Braster’s proprietary technology. The aim of this study was to develop a computer system, using a client-server architecture, to an automatic interpretation of thermographic pictures created by the Braster devices.