GAN4Seg is a project focused on developing Generative AI models to segment Brain CT and MRI scans through machine learning methodologies.
Many neurological experts depend on radiologists and other medical experts to take and analyze CT scans, specifically to differentiate between skin, bone, and tissue, among other components in medical images. However, this is often a time-intensive and very manual process for radiologists and neurologists to complete. GAN4Seg hopes to contribute to the medical community by integrating modern AI-based image processing systems with medical processes to improve MRI and CT analysis times, improving patient care.
GAN4Seg aims to use generational adversarial networks (GANs) to drive the training of machine learning algorithms which will further process the contents of MRI and CT scans into useful features that can be identified and used by a medical professional. We hope that the model developed through this project aids physiological analyses of patients and reduces pressure within decision-making situations in a surgical context. This model seeks to aid in improving and increasing efficiency within the diagnostic decision-making prior to surgery.
This model will be built to aid and serve surgeons and medical professionals, however, future work may focus on patient-facing diagnostics.