Shypd.aiThe largest open index of AI toolsretina-unet is an open-source convolutional neural network for segmenting blood vessels in retina fundus images. It uses a U-Net architecture and achieves high accuracy on DRIVE and STARE databases.
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retina-unet is an open-source convolutional neural network specifically designed for the segmentation of blood vessels in retina fundus images. Based on the U-Net architecture, this tool performs a binary classification task, identifying each pixel as either a vessel or not. It has been rigorously tested on the DRIVE and STARE databases, demonstrating superior performance in terms of area under the ROC curve compared to other methods. The repository provides the implementation in Python, utilizing the Keras library with either Theano or TensorFlow backends. It includes detailed instructions for data preparation, training with sub-images (patches), and evaluating the trained model, making it a valuable resource for medical image analysis and research.
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