TY - JOUR A1 - Pfeil, Juliane A1 - Nechyporenko, Alina A1 - Frohme, Marcus A1 - Hufert, Frank T. A1 - Schulze, Katja T1 - Examination of blood samples using deep learning and mobile microscopy TI - BMC Bioinformatics N2 - Microscopic examination of human blood samples is an excellent opportunity to assess general health status and diagnose diseases. Conventional blood tests are performed in medical laboratories by specialized professionals and are time and labor intensive. The development of a point-of-care system based on a mobile microscope and powerful algorithms would be beneficial for providing care directly at the patient's bedside. For this purpose human blood samples were visualized using a low-cost mobile microscope, an ocular camera and a smartphone. Training and optimisation of different deep learning methods for instance segmentation are used to detect and count the different blood cells. The accuracy of the results is assessed using quantitative and qualitative evaluation standards. Y1 - 2022 UR - https://opus4.kobv.de/opus4-th-wildau/frontdoor/index/index/docId/1580 UR - https://nbn-resolving.org/urn:nbn:de:kobv:526-opus4-15802 SN - 1471-2105 VL - 23 PB - BioMed Central ER -