Image-based recognition of surgical instruments by means of convolutional neural networks

ConclusionWith recognition accuracies of up to 99.9% on a highly meaningful test data set, recognition of surgical instruments is suitable for many track and trace applications in the hospital. But the system has limitations: A homogeneous background and controlled lighting conditions are required. The detection of multiple instruments in one image in front of various backgrounds is part of future work.
Source: International Journal of Computer Assisted Radiology and Surgery - Category: Intensive Care Source Type: research