Spatial variable extraction from digital slides using deep-learning, affinity-propagation clustering, and spatial statistics. (A) Left to right: Whole-slide image scan of an OCT2-stained tissue section of NLPHL with Fan pattern “C.” A highlighted 256 × 256-pixel tile is magnified in panel C. The planar point pattern after cell detection, showing LP cell and B-cell centroids. LP cell clusters are identified using affinity-propagation clustering. (B) Planar point pattern and result of affinity-propagation clustering of LP cell centroids in an NLPHL case with Fan pattern “A.” A specific cluster is highlighted in both the point pattern and cluster plot. (C) Individual tiles with detected cells enclosed within bounding boxes. The deep-learning detection precision was 95.43%. (D) Point patterns of the tiles with symbols indicating different cell types and spatial variables, including the area of bounding boxes as an approximation of the nuclear area, nearest neighbor distances between cell centroids, and point counts for cell density calculation.