Figure 2 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies
Yeman Brhane Hagos, Catherine S.Y. Lecat, Dominic Patel, Anna Mikolajczak, Simón P. Castillo, Emma J. Lyon, Kane A. Foster, Thien-An Tran, Lydia S.H. Lee, Manuel Rodriguez‐Justo, Kwee Yong, Yinyin Yuan · 2024
Computational methods for bone thickness analysis and cell infiltration patterns: A, Image analysis to estimate bone thickness (Supplementary Materials and Methods). Using the same BM sample image as Fig. 1A, the bone segmentation (ii) is an output of MoSaicNet (Supplementary Materials and Methods), and each bone is displayed in a different color. The color bar shows the pixel intensity of the image in iii and iv. The pixel intensity on the skeleton indicates half of the bone thickness (Supplementary Materials and Methods). B, Cell infiltration pattern analysis using NND and the null hypothesis of CSR (Supplementary Materials and Methods). Z 1.96, and −1.96 ≤ Z ≤ 1.96 indicate a clustered, dispersed, and random distribution of observed cells, respectively. std, standard deviation; μ, mean NND of CSR.