SAM for Medical Imaging. Segment Anything Model from Meta

The Segment Anything Model (SAM) is a state-of-the-art image segmentation model that was introduced by Meta. The SAM model is designed to be promptable, which means that it can generalize to new image distributions and tasks beyond those seen during training. This capability is achieved through the use of prompt engineering, where hand-crafted text is used to prompt the model to generate a valid response for the task at hand. SAM has three main components: an image encoder, a flexible prompt encoder, and a fast mask decoder. The image encoder uses a pre-trained Vision Transformer (ViT) that is adapted to process high-resolution inputs.