This tutorial provides a step-by-step guide on how to implement and train a U-Net model for Melanoma detection using TensorFlow/Keras. What You’ll Learn : Data Preparation: We’ll begin by showing you how to access and preprocess a substantial dataset of Melanoma images and corresponding masks. Data Augmentation: Discover the techniques to augment your dataset. It will increase and improve your model’s results Model Building: Build a U-Net, and learn how to construct the model using TensorFlow and Keras. Model Training: We’ll guide you through the training process, optimizing your model to distinguish Melanoma from non-Melanoma skin lesions. Testing and Evaluation: Run the pre-trained model on a new fresh images . Explore how to generate masks that highlight Melanoma regions within the images. Visualizing Results: See the results in real-time as we compare predicted masks with actual ground truth masks. You can find link for the code in the blog : https://eranfeit.net/medical-melanoma-detection-tensorflow-u-net-tutorial-using-unet/ Full code description for Medium users : https://medium.com/@feitgemel/medic...orflow-u-net-tutorial-using-unet-c89e926e1339 You can find more tutorials, and join my newsletter here : https://eranfeit.net/ Check out our tutorial here : Enjoy Eran #Python #openCV #TensorFlow #Deeplearning #ImageSegmentation #Unet #Resunet #MachineLearningProject #Segmentation
