A platform-independent framework for phenotyping of multiplex tissue imaging data
Fig 2
Removal of various artifacts and noise from MIBI data.
A: An example of cross-channel contamination where a contaminating signal from hepatocyte antigen channel, the oxide of the metal Neodymium (145 m/z + 16 m/z, top), contaminates a target channel, CD20 with Dysprosium (161 m/z, middle). The contamination is removed in the FR map (bottom). The histograms of pixel values for the insets (highlighted in yellow) of the images are displayed both before and after artifacts correction. B: Section of Ki-67 marker from ovarian cancer tissue before (left) and after(right) gold removal (a MIBI platform artifact). C: Section of breast tissue stained with pan-cytokeratin antibodies before (left) and after (right) removal of necrotic tissue regions. Histograms of pixel values are included for all images (A-C) before and after artifacts correction. D: Section of ovarian cancer tissue stained with CD163 antibody before (left) and after noise and aggregates (right) correction. Corresponding histograms of pixel values for the pseudo-cells outlined in green, orange, and red are plotted before and after noise and aggregate correction. E: CD11c staining of lung tissue by IMC (left) and the corresponding FR map (right). F: CD8 staining of ovarian cancer tissue by MIBI (left) and the corresponding FR map (right). One classifier is trained for each of the individual raw images shown in panels A-F.