Susan Strong, Susan Baptiste, Donald Cole, Judith Clarke, Marcos Costa, Harry Shannon, Rhoda Reardon, Sandra Sinclair
Functional assessment of injured workers: a profile of assessor practices
Canadian journal of occupational therapy. Revue canadienne d'ergotherapie
latent diffusion models ldms emerged stateoftheart image generation method outperforming previous generative adversarial networks gans terms training stability image quality computational pathology generative models valuable data sharing data augmentation however impact ldmgenerated images histopathology tasks compared traditional gans systematically studied trained three ldms stylegan2 model histology tiles nine colorectal cancer crc tissue classes ldms include 1 finetuned version stable diffusion v14 2 kullbackleibler klautoencoder klf8dm 3 vector quantized vqautoencoder deploying ldm vqf8dm assessed image quality expert ratings dimensional reduction methods distribution similarity measures impact training multiclass tissue classifier additionally investigated image memorization klf8dm stylegan2 models models provided high image quality klf8dm achieving best frechet inception distance fid expert rating scores complex tissue classes simpler classes vqf8dm stylegan2 models performed better image memorization negligible stylegan2 klf8dm models classifiers trained mix klf8dm generated real images achieved 4 improvement overall classification accuracy highlighting usefulness images dataset augmentation systematic study generative methods showed klf8dm produces highest quality images negligible image memorization higher classifier performance generatively augmented dataset suggests augmentation technique employed enhance histopathology classifiers various tasks