MoMic is a platform for point-of-care digital microscopy diagnostics, supported by artificial intelligence-based image analysis.
The first applications include digital diagnostics for cervical cancer, malaria, soil-transmitted helminth infections and schistosomiasis. The device is constructed mainly using cheap, plastic components from consumer electronic products, such as smartphone camera systems, resulting in material costs orders of magnitude cheaper than conventional digital slide scanners (approximately the price of a mid-range camera phone). The device enables point-of-care digitization of microscopy samples, such as blood smear or cytological samples, which can be instantaneously uploaded wirelessly over local data networks to a central server. Here, machine learning algorithms based on convolutional neural networks can be utilized to analyze the samples, detect areas of interest, such as infectious pathogens or pre-cancerous cells, and relay the results back to the point-of-care as diagnostic aid. Scanned samples can also be viewed remotely, e.g. using mobile phones or computers, thus further reducing the need for trained experts at the point-of-care.