We’re excited to announce that our patent applications have been approved.
Noise-resilient vasculature localization method with regularized segmentation
The present invention relates to a method for neural network training for near-infrared vein imaging, the method including obtaining a set of raw images based on near-infrared radiation from vein; pre-processing the set of raw images using a filter and/or an adaptive filter, and/or a denoising network to enhance the visibility of veins and applying an annotation tool for removing the noise and for generating annotated ground truth masks; splitting the pre-processed images into a training set and a test set; feeding the training set and the test set to the neural network; calculating the gradient of loss to evaluate the accuracy of the neural network predictions based on the annotated masks; searching a set of weights and biases that minimizes the losses with the annotated masks; penalizing the neural network for mistakes of the first kind using loss function and/or a tube-like minimal path method. The present method allows a clear definition of a vein contour.
More details at Google patents: