Create a 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');

Specify the location of all complete blocks of size 768-by-1024.

bls = selectBlockLocations(bim,'BlockSize',[768 1024], ...
    'ExcludeIncompleteBlocks',true);

Visualize the block locations as rectangular ROIs overlaid on the big image. The drawrectangle function expects the size of the ROI to be specified in (width,height) form, so horizontally flip the block size of the blockLocationSet, which is specified in (height,width) form.

bigimageshow(bim)
blockWH = fliplr(bls.BlockSize);
for ind = 1:size(bls.BlockOrigin,1)
    drawrectangle('Position',[bls.BlockOrigin(ind,:),blockWH]);
end

Create a 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');

Specify the size of blocks to read.

blockSize = [1500 1500];

To overlap blocks, specify a block offset distance that is less than the block size.

blockOffsets = blockSize - 150;

Specify the location of complete blocks in the image using the block size and block offset distance.

bls = selectBlockLocations(bim,...
      'BlockSize',blockSize,...
      'BlockOffSets',blockOffsets,...
      'ExcludeIncompleteBlocks',true);

Visualize the block locations as rectangular ROIs overlaid on the big image. Display each ROI in a different color.

bigimageshow(bim)
blockWH = fliplr(bls.BlockSize);
colors = prism(size(bls.BlockOrigin,1));
for ind = 1:size(bls.BlockOrigin,1)
    blockColor = colors(ind,:);
    drawrectangle('Position',[bls.BlockOrigin(ind,:),blockWH],'Color',blockColor);
end

Create a 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');

Specify the size of blocks to read.

blockSize = [1024 512];

Specify the block offset distance as 1.5 times the block size.

blockOffsets = 1.5*blocksize;

Specify the location of complete blocks in the image using the block size and block offset distance. The resulting blockLocationSet object has 21 blocks.

bls = selectBlockLocations(bim,...
      'BlockSize',blockSize,...
      'BlockOffSets',blockOffsets,...
      'ExcludeIncompleteBlocks',true);

Visualize the block locations as rectangular ROIs overlaid on the big image.

bigimageshow(bim)
blockWH = fliplr(bls.BlockSize);
for ind = 1:size(bls.BlockOrigin,1)
    drawrectangle('Position',[bls.BlockOrigin(ind,:),blockWH]);
end

Create a bigimageDatastore that reads blocks from the locations specified in the blockLocationSet object.

numBlocks = length(bls.BlockOrigin);
bimds = bigimageDatastore(bim,'BlockLocationSet',bls, ...
    'ReadSize',numBlocks);

Read all blocks in the datastore and display the blocks as a montage. The block data agrees with the block location ROIs overlaid on the bigimage.

blocks = read(bimds);
figure
montage(blocks,'Size',[3 7],'BorderSize',5,'BackgroundColor','k');

Create a 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 bigimage by using the bigimageshow function.

h = bigimageshow(bim);

Create a mask at the coarsest resolution level, retaining the original spatial referencing information.

clevel = bim.CoarsestResolutionLevel;
imcoarse = getFullLevel(bim,clevel);
stainMask = ~imbinarize(rgb2gray(imcoarse));
bmask = bigimage(stainMask,'SpatialReferencing',bim.SpatialReferencing(clevel));

Specify the location of blocks to read from the bigimage by using the selectBlockLocations function. Set the block size as 256-by-256 pixels. Select blocks that are at least 75% within the ROI defined by the mask by specifying the 'InclusionThreshold' name-value pair argument. By default, selectBlockLocations selects blocks from the finest resolution level of the big image.

t = 0.75;
blockSize = [256 256];
blockSet = selectBlockLocations(bim,"BlockSize",blockSize, ...
    "Masks",bmask,"InclusionThreshold",t);

Create a bigimageDatastore that reads four blocks at a time from the locations specified by the blockLocationSet.

bimds = bigimageDatastore(bim,"BlockLocationSet",blockSet,"ReadSize",4);

To preview which patches are read by the datastore, display the mask over the original bigimage using the same block size and inclusion threshold. The overlay highlights in green the patches that are at least 75% within the ROI defined by the mask.

showmask(h,bmask,'BlockSize',blockSize,'InclusionThreshold',t)

Read the first batch of data from the datastore and display the returned image patches as a montage. The content of these patches matches the green blocks of the overlay.

blocks = read(bimds);
montage(blocks,'Size',[1 bimds.ReadSize],'BorderSize',5,'BackgroundColor','k');