Medical image segmentation is an innovative process that enables surgeons to have a virtual "x-ray vision." It is a highly valuable tool in healthcare, providing non-invasive diagnostics and in-depth ...
Enhancing Medical Multi-Label Image Classification Using PyTorch & Lightning
In the pivotal field of medical diagnostics, swift and accurate image classification plays a crucial role in aiding healthcare professionals' decision-making. The advent of deep learning, coupled with ...
Transfer Learning for Medical Images
Our consulting company, Big Vision, has a long history of solving challenging computer vision and AI problems in diverse fields ranging from document analysis, security, manufacturing, real estate, ...
MRNet – The Multi-Task Approach
Our last post on the MRNet challenge presented a simple way to approach it. There you learned to make a separate model for each disease. And ended up with three models. Time to up your game! Now ...
Stanford MRNet Challenge: Classifying Knee MRIs
Stanford ML Group, led by Andrew Ng, works on important problems in areas such as healthcare and climate change, using AI. Last year they released a knee MRI dataset consisting of 1,370 knee MRI ...