Get all data in one level of big image
bigimage using a modified version of image "tumor_091.tif" from the CAMELYON16 data set. The original image is a training image of a lymph node containing tumor tissue. The original image has eight resolution levels, and the finest level has resolution 53760-by-61440. The modified image has only three coarse resolution levels. The spatial referencing of the modified image has been adjusted to enforce a consistent aspect ratio and to register features at each level.
bim = bigimage('tumor_091R.tif');
Display the entire
bigimage at the finest resolution level. Display a grid of the block boundaries.
bshow = bigimageshow(bim,'GridVisible','on','GridLevel',1);
Determine the coarsest resolution level and the spatial referencing of the
bigimage at that level.
clevel = bim.CoarsestResolutionLevel; clevelLims = bim.SpatialReferencing(clevel);
Create a mask of the coarsest resolution level by following these steps:
Get a single-resolution image of the coarsest resolution level.
Convert the image to grayscale.
Binarize the image. In the binarized image, the object of interest is black and the background is white.
Take the complement of the binarized image. The resulting mask follows the convention in which the object of interest is white and the background is black.
imcoarse = getFullLevel(bim,clevel); graycoarse = rgb2gray(imcoarse); bwcoarse = imbinarize(graycoarse); mask = imcomplement(bwcoarse);
bigimage containing the mask. Use the same spatial referencing as the original big image.
bmask = bigimage(mask,'SpatialReferencing',clevelLims);
Display the mask.
Overlay the mask on the original
bigimage. To highlight all blocks that contain at least one nonzero mask pixel, specify an inclusion threshold of
I— Single-resolution image
Single-resolution image, returned as a numeric array.