diff --git a/src/main/java/io/bioimage/modelrunner/tiling/TileCalculator.java b/src/main/java/io/bioimage/modelrunner/tiling/TileCalculator.java
index 11350998..481a2c55 100644
--- a/src/main/java/io/bioimage/modelrunner/tiling/TileCalculator.java
+++ b/src/main/java/io/bioimage/modelrunner/tiling/TileCalculator.java
@@ -1,13 +1,17 @@
 package io.bioimage.modelrunner.tiling;
 
 import java.util.Arrays;
+import java.util.LinkedHashMap;
 import java.util.List;
 import java.util.stream.Collectors;
+import java.util.stream.IntStream;
 
 import io.bioimage.modelrunner.bioimageio.TileFactory;
 import io.bioimage.modelrunner.bioimageio.description.Axis;
 import io.bioimage.modelrunner.bioimageio.description.ModelDescriptor;
 import io.bioimage.modelrunner.bioimageio.description.TensorSpec;
+import io.bioimage.modelrunner.tensor.Tensor;
+import net.imglib2.RandomAccessibleInterval;
 
 public class TileCalculator {
 	
@@ -17,6 +21,10 @@ public class TileCalculator {
 	
 	private final TileFactory factory;
 	
+	private final LinkedHashMap<String, PatchSpec> input = new LinkedHashMap<String, PatchSpec>();
+	
+	private final LinkedHashMap<String, PatchSpec> output = new LinkedHashMap<String, PatchSpec>();
+	
 	private TileCalculator(ModelDescriptor descriptor, List<TileInfo> tileInfoList) {
 		this.descriptor = descriptor;
 		this.tileInfoList = tileInfoList;
@@ -28,14 +36,13 @@ public static TileCalculator build(ModelDescriptor descriptor, List<TileInfo> ti
 		return new TileCalculator(descriptor, tileInfoList);
 	}
 	
-	private boolean validate() {
+	private void validate() {
 		checkAllTensorsDefined();
 		validateTileVsImageSize();
 		validateStepMin();
 		validateTileVsHalo();
 		validateTileVsImageChannel();
 		checkTilesCombine();
-		return false;
 	}
 	
 	private void validateTileVsHalo() {
@@ -163,7 +170,64 @@ private void checkAllTensorsDefined() {
 	}
 	
 	private void calculate() {
+		for (TensorSpec tt : this.descriptor.getInputTensors()) {
+			TileInfo tile = tileInfoList.stream()
+					.filter(til -> til.getName().equals(tt.getTensorID())).findFirst().orElse(null);
+			input.put(tt.getTensorID(), computePatchSpecs(tt, tile));
+		}
 	}
+
+    /**
+     * Compute the patch details needed to perform the tiling strategy. The calculations
+     * obtain the input patch, the padding needed at each side and the number of patches
+     * needed for every tensor.
+     * 
+     * @param spec
+     * 	specs of the tensor
+     * @param rai
+     * 	ImgLib2 rai, backend of a tensor, that is going to be tiled
+     * @param tileSize
+     * 	the size of the tile selected to process the image
+     * 
+     * @return an object containing the specs needed to perform patching for the particular tensor
+     */
+    private PatchSpec computePatchSpecs(TensorSpec spec, TileInfo tile)
+    {
+    	long[] imSize = arrayToWantedAxesOrderAddOnes(tile.getImageDimensions(), 
+    			tile.getImageAxesOrder(), spec.getAxesInfo().getAxesOrder());
+    	long[] tileSize = arrayToWantedAxesOrderAddOnes(tile.getProposedTileDimensions(), 
+    			tile.getTileAxesOrder(), spec.getAxesInfo().getAxesOrder());
+        int[][] paddingSize = new int[2][tileSize.length];
+        // REgard that the input halo represents the output halo + offset 
+        // and must be divisible by 0.5. 
+        int[] halo = spec.getHaloArr();
+        if (!descriptor.isPyramidal() && this.descriptor.isTilingAllowed()) {
+        	// In the case that padding is asymmetrical, the left upper padding has the extra pixel
+            for (int i = 0; i < halo.length; i ++) {paddingSize[0][i] = (int) Math.ceil(halo[i]);}
+            // In the case that padding is asymmetrical, the right bottom padding has one pixel less
+            for (int i = 0; i < halo.length; i ++) {paddingSize[1][i] = (int) Math.floor(halo[i]);}
+            
+        }
+        int[] patchGridSize = new int[imSize.length];
+        for (int i = 0; i < patchGridSize.length; i ++) patchGridSize[i] = 1;
+        if (descriptor.isTilingAllowed()) {
+            patchGridSize = IntStream.range(0, tileSize.length)
+                    .map(i -> (int) Math.ceil((double) imSize[i] / ((double) tileSize[i] - halo[i] * 2)))
+                    .toArray();
+        }
+        // For the cases when the patch is bigger than the  image size, share the
+        // padding between both sides of the image
+        paddingSize[0] = IntStream.range(0, tileSize.length)
+                .map(i -> 
+                	(int) Math.max(paddingSize[0][i],
+                			Math.ceil( (double) (tileSize[i] - imSize[i]) / 2))
+                ).toArray();
+        paddingSize[1] = IntStream.range(0, tileSize.length)
+            .map(i -> (int) Math.max( paddingSize[1][i], 
+            		tileSize[i] - imSize[i] - paddingSize[0][i])).toArray();
+
+        return PatchSpec.create(spec.getTensorID(), tileSize, patchGridSize, paddingSize, imSize);
+    }
 	
 	public void getTileList() {