Improving Feature Extraction from Histopathological Images Through A Fine-tuning ImageNet Model. (arXiv:2201.00636v1 [eess.IV])

Due to lack of annotated pathological images, transfer learning has been the
predominant approach in the field of digital pathology.Pre-trained neural
networks based on ImageNet database are often used to extract "off the shelf"
features, achieving great success in predicting tissue types, molecular
features, and clinical outcomes, etc. We hypothesize that fine-tuning the
pre-trained models using histopathological images could further improve feature
extraction, and downstream prediction performance.We used 100,000 annotated HE
image patches for colorectal cancer (CRC) to finetune a …

arxiv fine-tuning imagenet