Synthesis of Annotated Colorectal Cancer Tissue Images from Gland Layout

arXiv:2305.05006v2 Announce Type: replace-cross
Abstract: Generating realistic tissue images with annotations is a challenging task that is important in many computational histopathology applications. Synthetically generated images and annotations are valuable for training and evaluating algorithms in this domain. To address this, we propose an interactive framework generating pairs of realistic colorectal cancer histology images with corresponding glandular masks from glandular structure layouts. The framework accurately captures vital features like stroma, goblet cells, and glandular lumen. Users can control gland appearance …

abstract algorithms annotations applications arxiv cancer computational cs.cv domain eess.iv framework generated images interactive synthesis training type