AI-based algorithm learns to detect tumours in microscopy images – Physics World

By applying deep-learning techniques to a set of phase-contrast microscopy images, Japanese researchers have been able to identify the nature and origin of different cancer cells with 96% accuracy. This approach could lead to better cancer treatments (Cancer Res. The researchers, from Osaka University, used a convolutional neural network (CNN), a common scheme used in deep learning, to analyse the images. CNNs work by applying to the input image a set of connected filters and mathematical functions that, similarly to neurons, can be trained to extract specific features. In medical imaging, CNNs are modelled on the human visual system, with low layers that capture fine details such as edges, and higher levels that capture complex features reflecting the whole image.