MRI images are understandably complex and data-heavy.
Because of this, developers training large language models (LLMs) for MRI analysis have had to slice captured images into 2D. But this results in just an approximation of the original image, thus limiting the model’s ability to analyze intricate anatomical structures. This creates challenges in complex cases involving brain tumors, skeletal…
