Reading notes: Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression
This blog is the reading note for the paper "Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression" by Ravi, Daniele, et al. MICCAI 2019. Broadly speaking, the authors try to simulating images representative of neurodegenerative diseases. Specifically, they designed a novel network named Degenerative Adversarial NeuroImage Net (DaniNet) to produce accurate and convincing synthetic images that emulate disease progression. Introduction Disease progression modelling help to map out longitudinal change during chronic diseases. However, modelling temporal neurodegeneration of full resolution MRI is still a challenging problem. Several traditional simulators proposed in the literature are extremely resource-demanding and is not scalable to high resolution image. [1] proposed a deep learning framework based on GAN to manipulate MRI, but their assumption is over-simplified: 1. disease progression is modelled linearly and 2. morphological chan