CNN-Diffusion-MRIBrain-Segmentation
In the rapidly advancing field of neuroscience, we heavily rely on brain MRI scans to diagnose diseases, assess injuries, and deepen our research. A key technique in our work is brain masking, where we isolate the brain tissue from surrounding structures such as the skull and skin. This isolation is crucial, as it allows us to focus our analysis exclusively on the brain, enabling more precise studies. Despite its critical role, brain masking has traditionally been a manual process. This method is slow and carries a high risk of human error, creating a significant bottleneck in our workflows. Furthermore, the existing automated tools available were unreliable, often failing because they relied on overly simplistic methods of geometric detection or outdated algorithms. Faced with these challenges, we turned to a more innovative solution: Convolutional Neural Networks (CNNs), a technology that has been successful in various industries for quick and accurate image segmentation.
Python, Computer Vision, Deep Learning