Research Findings from King Faisal University Update Understanding of Diagnostics [Few-Shot Learning for Medical Image Segmentation Using 3D U-Net and Model-Agnostic Meta-Learning (MAML)].

A research study conducted at King Faisal University in Saudi Arabia explores the use of few-shot learning techniques in medical image segmentation. The study focuses on the application of a gradient-based method called Model-Agnostic Meta-Learning (MAML) and an enhanced 3D U-Net convolutional neural network for segmenting liver, spleen, and kidney images. The results show that the approach allows for rapid adaptation to new tasks with only a few annotated images, achieving high mean dice coefficients for segmentation accuracy. The study concludes by assessing the effectiveness of the proposed approach on a dataset from a local hospital. [Extracted from the article]