Fig. 1: Overview of proposed UNMaSk pipeline for DCIS detection and segmentation.
From: Unmasking the immune microecology of ductal carcinoma in situ with deep learning
a UNet architecture for tissue segmentation and one of the existing deep learning methods, single-shot detector (SSD) architecture, used for DCIS detection. b Spatial Voronoi tessellation to examine local tissue ecology for each DCIS duct, based on deep learning results on DCIS segmentation and single-cell classification. Examples shown are immune depleted and immune predominant/inflamed ecology local to individual DCIS ducts and spatial analysis using DCIS immune colocalisation/Morisita Score (MS).
