Synthesizing histopathology images to develop algorihtms predicting cancerous lung tissue
This project stream involves the partners at LMU as domain experts in pathology, the partners at Fraunhofer HHI, Aignostics and Dotphoton as technical experts.
Synthesizing brain MRIs to develop algorithms predicting dementia-related abnormalities.
This project stream involves the partners at MDC as domain experts in MR imaging, the HPI and partners at Imfusion as technical experts.
We trained a conditional StyleGAN3 with a transfer-causal inference step (Manuscript will follow soon) on T1 structural brain MR images from the Alzheimer's Disease Neuroimaging Initiative (ADNI). For training, we used 2D coronal mid-slice brain MRIs and conditioned on Age, Sex, clinical dementia rating (CDR) and the brain structure (volumes). Using an inference step with transfer-learning and a causal model, the GAN learned the relationship between conditional variables and the brain structure. We generated new images with corresponding labels of either ‘cognitive normal’ (CDR Score=0), ‘mild cognitive impairment’ (CDR Score=0.5) or ’Alzheimer’s Disease (CDR Score=1), with the covariates age and sex. The generated images and labels can be downloaded here.
