LC3B ROI Quantification

The function reads in 16-bit images in the form of multidimensional (3D) tiff stacks. The function requires that the third-dimension be the image channels (n=3) and ordered with the nuclear marker first, signal that you would like to quantify second and the channel which contains the pathogen last. The x, y dimensions are flexible, and the function can take in almost any size 2D array.

The function will first deinterleave the multidimensional tiff stacks and process each channel separately. The function will then define thresholds for all three channels, undergo watershed segmentation for the first and third channels and quantify the number of bacteria and nuclei present in the entire image.

Next the function will take the pathogens that were identified and create a defined region of interest (ROI) with the bacteria as the centroid of the ROI. Each ROI in the image is labeled and run through regionprops to get the bounding box for all ROIs. The function imcrop and the bounding boxes for each ROI are used create a sub-plot of sub-images showing the ROI, identified bacteria and the associated binary mask used to extract the intracellular signal surrounding the pathogen. The subplot will contain sub-images of all the ROIs identified in an image and will be exported to the out-directory as a tiff with the same name as the input file.

The total number of bacteria and nuclei identified for each image will be exported to separate excel files that are saved to the working directory. Additionally, each ROIs integrated density from objects surrounding the pathogen is quantified separately and all the individual results for the ROIs are exported to an excel file sequentially. The function will also label the sheet tabs with the original image name, which contains the ROI data extracted from that image.

Please contact author for demo images of RAW 264.7 cells infected with SL1344 sif::B GFP.