The world of medical imaging is often dominated by complex and resource-heavy tools. These tools, while powerful, can be out of reach for many. This is particularly true in places where resources are scarce, such as low-income countries, rural clinics, and areas affected by conflict. The use of advanced imaging technologies in these settings is often limited by the n...

Imagine trying to teach a computer to understand medical images, but you don't have enough examples to show it. This is a big challenge in medical image segmentation, where computers try to identify specific parts of an image. One solution is semi-supervised learning, where the computer can learn from both labeled and unlabeled data. Medical image segmentati...