Better, faster and lighter diffusion models for medical diagnosis
8 November 2024
Imaging is a key tool in medical diagnosis but images can be ‘noisy’, making their analysis challenging. Our project addresses the limitations in the fields of image reconstruction and denoising by leveraging diffusion models and plug-and play methods. We are focusing on their theoretical foundations and practical applications, particularly in the medical domain. Our project, called “From Theory to Treatment: Advancing Diffusion Models for Medical Diagnosis,” it is one of 11 projects funded through the 2023 Accelerate Programme and Cambridge Centre for Data Driven Discovery (C2D3) funding call.
